Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator,
2021
HTML Version.
Code, Recurrent Networks.
Code, Monocular Depth.
Dataset, Monocular Depth.
Choi, S.H.[Sung-Hwan],
Min, D.B.[Dong-Bo],
Ham, B.[Bumsub],
Kim, Y.J.[Young-Jung],
Oh, C.J.[Chang-Jae],
Sohn, K.H.[Kwang-Hoon],
Depth Analogy: Data-Driven Approach for Single Image Depth Estimation
Using Gradient Samples,
IP(24), No. 12, December 2015, pp. 5953-5966.
IEEE DOI
1512
Poisson distribution
BibRef
Jung, H.,
Kim, Y.J.[Young-Jung],
Min, D.B.[Dong-Bo],
Oh, C.J.[Chang-Jae],
Sohn, K.H.[Kwang-Hoon],
Depth prediction from a single image with conditional adversarial
networks,
ICIP17(1717-1721)
IEEE DOI
1803
Databases, Estimation, Generators, Periodic structures,
Spatial resolution, Training, Depth from a single image,
generative adversarial learning
BibRef
Kim, Y.J.[Young-Jung],
Min, D.B.[Dong-Bo],
Ham, B.[Bumsub],
Sohn, K.H.[Kwang-Hoon],
Fast Domain Decomposition for Global Image Smoothing,
IP(26), No. 8, August 2017, pp. 4079-4091.
IEEE DOI
1707
concave programming, decomposition,
least squares approximations, minimisation,
computational photography application,
edge-preserving smoothing,
BibRef
Kim, Y.J.[Young-Jung],
Jung, H.,
Min, D.B.[Dong-Bo],
Sohn, K.H.[Kwang-Hoon],
Deeply Aggregated Alternating Minimization for Image Restoration,
CVPR17(284-292)
IEEE DOI
1711
Algorithm design and analysis, Data models, Image reconstruction,
Image restoration, Minimization, Neural networks, Optimization
BibRef
Kim, S.[Sunok],
Choi, S.H.[Sung-Hwan],
Sohn, K.H.[Kwang-Hoon],
Learning depth from a single image using visual-depth words,
ICIP15(1895-1899)
IEEE DOI
1512
K-means clustering
BibRef
Kim, Y.J.[Young-Jung],
Choi, S.H.[Sung-Hwan],
Sohn, K.H.[Kwang-Hoon],
Data-driven single image depth estimation using weighted median
statistics,
ICIP14(3808-3812)
IEEE DOI
1502
Based on matches to similar images.
Wrong section, one of several, learn patterns from other images, apply.
BibRef
Herrera, J.L.[Jose L.],
del-Bianco, C.R.[Carlos R.],
García, N.[Narciso],
Automatic Depth Extraction from 2D Images Using a Cluster-Based
Learning Framework,
IP(27), No. 7, July 2018, pp. 3288-3299.
IEEE DOI
1805
BibRef
Earlier:
Learning 3D structure from 2D images using LBP features,
ICIP14(2022-2025)
IEEE DOI
1502
feature extraction, image colour analysis, image convertors,
image filtering, image representation, image segmentation,
machine learning
BibRef
Herrera, J.L.[Jose L.],
Konrad, J.[Janusz],
del-Bianco, C.R.[Carlos R.],
Garcia, N.[Narciso],
Learning-based depth estimation from 2D images using GIST and
saliency,
ICIP15(4753-4757)
IEEE DOI
1512
2D-to-3D Image Conversion; Depth maps; GIST Descriptor; Saliency.
Color
BibRef
Zhang, Z.,
Xu, C.,
Yang, J.,
Gao, J.,
Cui, Z.,
Progressive Hard-Mining Network for Monocular Depth Estimation,
IP(27), No. 8, August 2018, pp. 3691-3702.
IEEE DOI
1806
data mining, estimation theory,
feature extraction, image colour analysis, image resolution,
recursive learning
BibRef
Bostan, E.,
Kamilov, U.S.,
Waller, L.,
Learning-Based Image Reconstruction via Parallel Proximal Algorithm,
SPLetters(25), No. 7, July 2018, pp. 989-993.
IEEE DOI
1807
image reconstruction, iterative methods,
learning (artificial intelligence), parallel algorithms,
statistical modeling
BibRef
Hou, B.,
Khanal, B.,
Alansary, A.,
McDonagh, S.,
Davidson, A.,
Rutherford, M.,
Hajnal, J.V.,
Rueckert, D.,
Glocker, B.,
Kainz, B.,
3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily
Oriented 2-D Images,
MedImg(37), No. 8, August 2018, pp. 1737-1750.
IEEE DOI
1808
Image reconstruction, Manuals, Robustness, image registration
BibRef
Mohaghegh, H.,
Karimi, N.,
Soroushmehr, S.M.R.,
Samavi, S.,
Najarian, K.,
Aggregation of Rich Depth-Aware Features in a Modified Stacked
Generalization Model for Single Image Depth Estimation,
CirSysVideo(29), No. 3, March 2019, pp. 683-697.
IEEE DOI
1903
BibRef
Earlier:
Single image depth estimation using joint local-global features,
ICPR16(727-732)
IEEE DOI
1705
Estimation, Training,
Semantics, Solid modeling,
modified stacked generalization model.
Monocular depth cues.
Correlation, Databases,
Data-driven approaches, Depth estimation,
Joint local-global framework, KNN regression model.
BibRef
Zeng, H.[Hui],
Zhang, R.[Ran],
Wang, X.Q.[Xiu-Qing],
Fu, D.M.[Dong-Mei],
Wei, Q.T.[Qing-Ting],
Dempster-Shafer evidence theory-based multi-feature learning and fusion
method for non-rigid 3D model retrieval,
IET-CV(13), No. 3, April 2019, pp. 261-266.
DOI Link
1904
BibRef
Shalaby, A.[Abdou],
Elmogy, M.[Mohammed],
Elfetouh, A.A.[Ahmed Abo],
3D image reconstruction from different image formats using marching
cubes technique,
IJCVR(9), No. 3, 2019, pp. 293-309.
DOI Link
1906
3D from any 2D image.
BibRef
Bartoli, A.E.[Adrien E.],
A Differential-Algebraic Projective Framework for the Deformable
Single-View Geometry of the 1D Perspective Camera,
JMIV(61), No. 7, September 2019, pp. 1051-1068.
WWW Link.
1908
Single-View Geometry (SVG) for the world-to-image mapping.
BibRef
Fan, B.[Bin],
Kong, Q.Q.[Qing-Qun],
Wang, X.C.[Xin-Chao],
Wang, Z.H.[Zhi-Heng],
Xiang, S.M.[Shi-Ming],
Pan, C.H.[Chun-Hong],
Fua, P.[Pascal],
A Performance Evaluation of Local Features for Image-Based 3D
Reconstruction,
IP(28), No. 10, October 2019, pp. 4774-4789.
IEEE DOI
1909
What features for 3D descriptions.
feature extraction, image capture, image classification,
image matching, image reconstruction, image sequences, Internet,
image matching
BibRef
Zheng, Y.[Yan],
Guo, B.L.[Bao-Long],
Yan, Y.Y.[Yun-Yi],
He, W.P.[Wang-Peng],
O2O Method for Fast 2D Shape Retrieval,
IP(28), No. 11, November 2019, pp. 5366-5378.
IEEE DOI
1909
Offline to offline.
Shape, Databases, Transform coding, Histograms, Graphical models,
Distribution functions, Measurement, Fast 2D shape retrieval,
shape descriptor
BibRef
Dai, R.Y.[Ren-Yue],
Gao, Y.B.[Yong-Bin],
Fang, Z.J.[Zhi-Jun],
Jiang, X.Y.[Xiao-Yan],
Wang, A.[Anjie],
Zhang, J.[Juan],
Zhong, C.S.[Ceng-Si],
Unsupervised learning of depth estimation based on attention model
and global pose optimization,
SP:IC(78), 2019, pp. 284-292.
Elsevier DOI
1909
Depth estimation, Attention model, Global pose optimization
BibRef
Wiles, O.[Olivia],
Zisserman, A.[Andrew],
Learning to Predict 3D Surfaces of Sculptures from Single and Multiple
Views,
IJCV(127), No. 11-12, December 2019, pp. 1780-1800.
Springer DOI
1911
BibRef
Earlier:
Wiles, O.[Olivia],
Zisserman, A.[Andrew],
3D Surface Reconstruction by Pointillism,
DeepLearn-G18(III:263-280).
Springer DOI
1905
BibRef
Moreau, A.[Ambroise],
Mancas, M.[Matei],
Dutoit, T.[Thierry],
Depth prediction from 2D images: A taxonomy and an evaluation study,
IVC(93), 2020, pp. 103825.
Elsevier DOI
2001
Depth prediction, Machine learning, Deep learning
BibRef
Zhang, Y.,
Feng, Y.,
Liu, X.,
Zhai, D.,
Ji, X.,
Wang, H.,
Dai, Q.,
Color-Guided Depth Image Recovery With Adaptive Data Fidelity and
Transferred Graph Laplacian Regularization,
CirSysVideo(30), No. 2, February 2020, pp. 320-333.
IEEE DOI
2002
Laplace equations, Color, Image color analysis, Task analysis,
Adaptation models, Image resolution, Optimization,
mixture probability maximization
BibRef
Koch, T.[Tobias],
Liebel, L.[Lukas],
Körner, M.[Marco],
Fraundorfer, F.[Friedrich],
Comparison of monocular depth estimation methods using geometrically
relevant metrics on the IBims-1 dataset,
CVIU(191), 2020, pp. 102877.
Elsevier DOI
2002
BibRef
Chen, W.[Wei],
Luo, X.[Xin],
Liang, Z.F.[Zheng-Fa],
Li, C.[Chen],
Wu, M.F.[Ming-Fei],
Gao, Y.M.[Yuan-Ming],
Jia, X.G.[Xiao-Gang],
A Unified Framework for Depth Prediction from a Single Image and
Binocular Stereo Matching,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Häne, C.[Christian],
Tulsiani, S.[Sohubham],
Malik, J.[Jitendra],
Hierarchical Surface Prediction,
PAMI(42), No. 6, June 2020, pp. 1348-1361.
IEEE DOI
2005
Geometry, Image color analysis, Shape,
Octrees, Color, Surface reconstruction, Single view reconstruction,
geometry prediction
BibRef
Zhao, D.[Dong],
Asano, Y.[Yuta],
Gu, L.[Lin],
Sato, I.[Imari],
Zhou, H.X.[Hui-Xin],
City-Scale Distance Sensing via Bispectral Light Extinction in Bad
Weather,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Ye, X.C.[Xin-Chen],
Zhang, M.L.[Ming-Liang],
Yang, J.Y.[Jing-Yu],
Fan, X.[Xin],
Guo, F.F.[Fang-Fang],
A sparsity-promoting image decomposition model for depth recovery,
PR(107), 2020, pp. 107506.
Elsevier DOI
2008
Image decomposition, Depth recovery, Depth discontinuities, Depth cameras
BibRef
Huang, S.F.[Shao-Fei],
Liu, S.[Si],
Hui, T.R.[Tian-Rui],
Han, J.Z.[Ji-Zhong],
Li, B.[Bo],
Feng, J.S.[Jia-Shi],
Yan, S.C.[Shui-Cheng],
ORDNet: Capturing Omni-Range Dependencies for Scene Parsing,
IP(29), 2020, pp. 8251-8263.
IEEE DOI
2008
Relative range.
Semantics, Convolution, Task analysis, Feature extraction,
Correlation, Cats, Visualization, Scene parsing, self-attention
BibRef
Mathew, A.[Alwyn],
Mathew, J.[Jimson],
Monocular depth estimation with SPN loss,
IVC(100), 2020, pp. 103934.
Elsevier DOI
2008
Depth estimation, Monocular depth estimation
BibRef
Luo, C.X.[Chen-Xu],
Yang, Z.H.[Zhen-Heng],
Wang, P.[Peng],
Wang, Y.[Yang],
Xu, W.[Wei],
Nevatia, R.[Ram],
Yuille, A.L.[Alan L.],
Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D
Holistic Understanding,
PAMI(42), No. 10, October 2020, pp. 2624-2641.
IEEE DOI
2009
Estimation, Optical imaging, Cameras,
Videos, Geometry, Task analysis, Depth estimation,
unsupervised learning
BibRef
Yang, Z.H.[Zhen-Heng],
Wang, P.[Peng],
Wang, Y.[Yang],
Xu, W.[Wei],
Nevatia, R.[Ram],
Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D
Motion Understanding,
ApolloScape18(V:691-709).
Springer DOI
1905
BibRef
Ye, X.C.[Xin-Chen],
Chen, S.[Shude],
Xu, R.[Rui],
DPNet: Detail-preserving network for high quality monocular depth
estimation,
PR(109), 2021, pp. 107578.
Elsevier DOI
2009
Depth estimation, Detail-preserving, Spatial, Attention, Depth map
BibRef
Rajeswar, S.[Sai],
Mannan, F.[Fahim],
Golemo, F.[Florian],
Parent-Lévesque, J.[Jérôme],
Vazquez, D.[David],
Nowrouzezahrai, D.[Derek],
Courville, A.[Aaron],
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using
a View-Based Representation,
IJCV(128), No. 10-11, November 2020, pp. 2478-2493.
Springer DOI
2009
BibRef
Liu, H.J.[Hua-Jun],
Lei, D.[Dian],
Zhu, Q.[Qing],
Sui, H.G.[Hai-Gang],
Zhang, H.R.[Huan-Ran],
Wang, Z.Y.[Zi-Yan],
Single-image depth estimation by refined segmentation and consistency
reconstruction,
SP:IC(90), 2021, pp. 116048.
Elsevier DOI
2012
Depth estimation, Image segmentation,
Consistency reconstruction, Single image
BibRef
Chen, H.X.,
Li, K.,
Fu, Z.,
Liu, M.,
Chen, Z.,
Guo, Y.,
Distortion-Aware Monocular Depth Estimation for Omnidirectional
Images,
SPLetters(28), 2021, pp. 334-338.
IEEE DOI
2102
Distortion, Convolution, Strips, Feature extraction, Estimation,
Training, Kernel, Depth estimation, deformable convolution,
omnidirectional images
BibRef
Raihan, A.J.[A. Jarina],
Abas, P.E.[Pg Emeroylariffion],
de Silva, L.C.[Liyanage C.],
Depth estimation for underwater images from single view image,
IET-IPR(14), No. 16, 19 December 2020, pp. 4188-4197.
DOI Link
2103
BibRef
Jiang, H.Z.[Hong-Zhi],
Li, Y.X.[Yu-Xi],
Zhao, H.J.[Hui-Jie],
Li, X.D.[Xu-Dong],
Xu, Y.[Yang],
Parallel Single-Pixel Imaging: A General Method for Direct-Global
Separation and 3D Shape Reconstruction Under Strong Global Illumination,
IJCV(129), No. 4, April 2021, pp. 1060-1086.
Springer DOI
2104
BibRef
And:
Correction:
IJCV(129), No. 5, May 2021, pp. 1787-1787.
Springer DOI
2105
Separation of direct and global illumination, to get 3D.
BibRef
Xue, F.[Feng],
Cao, J.F.[Jun-Feng],
Zhou, Y.[Yu],
Sheng, F.[Fei],
Wang, Y.[Yankai],
Ming, A.[Anlong],
Boundary-induced and scene-aggregated network for monocular depth
prediction,
PR(115), 2021, pp. 107901.
Elsevier DOI
2104
Monocular depth prediction, Boundary-induced, Depth correlation
BibRef
Xu, X.F.[Xian-Fa],
Chen, Z.[Zhe],
Yin, F.L.[Fu-Liang],
Monocular Depth Estimation With Multi-Scale Feature Fusion,
SPLetters(28), 2021, pp. 678-682.
IEEE DOI
2104
Convolution, Feature extraction, Estimation, Training, Fuses,
Task analysis, Kernel, Attention,
multi-scale feature fusion
BibRef
Xu, X.F.[Xian-Fa],
Chen, Z.[Zhe],
Yin, F.L.[Fu-Liang],
Multi-Scale Spatial Attention-Guided Monocular Depth Estimation With
Semantic Enhancement,
IP(30), 2021, pp. 8811-8822.
IEEE DOI
2111
Estimation, Semantics, Mutual information, Feature extraction,
Correlation, Cameras, Visualization, Depth estimation,
semantic enhancement
BibRef
Ye, X.C.[Xin-Chen],
Fan, X.[Xin],
Zhang, M.L.[Ming-Liang],
Xu, R.[Rui],
Zhong, W.[Wei],
Unsupervised Monocular Depth Estimation via Recursive Stereo
Distillation,
IP(30), 2021, pp. 4492-4504.
IEEE DOI
2105
Estimation, Training, Testing, Knowledge engineering,
Recursive estimation, Network architecture, Image reconstruction,
recursive
BibRef
Song, X.B.[Xi-Bin],
Li, W.[Wei],
Zhou, D.F.[Ding-Fu],
Dai, Y.C.[Yu-Chao],
Fang, J.[Jin],
Li, H.D.[Hong-Dong],
Zhang, L.J.[Liang-Jun],
MLDA-Net: Multi-Level Dual Attention-Based Network for
Self-Supervised Monocular Depth Estimation,
IP(30), 2021, pp. 4691-4705.
IEEE DOI
2105
BibRef
Xu, W.P.[Wan-Peng],
Zou, L.[Ling],
Wu, L.D.[Ling-Da],
Fu, Z.P.[Zhi-Peng],
Self-Supervised Monocular Depth Learning in Low-Texture Areas,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Zhang, N.[Ning],
Nex, F.[Francesco],
Vosselman, G.[George],
Kerle, N.[Norman],
Lite-Mono: A Lightweight CNN and Transformer Architecture for
Self-Supervised Monocular Depth Estimation,
CVPR23(18537-18546)
IEEE DOI
2309
BibRef
Madhuanand, L.[Logambal],
Nex, F.[Francesco],
Yang, M.Y.[Michael Ying],
Self-supervised monocular depth estimation from oblique UAV videos,
PandRS(176), 2021, pp. 1-14.
Elsevier DOI
2106
Depth estimation, Monocular, UAV video,
Self-supervised learning, Scene Understanding
BibRef
Su, W.[Wen],
Zhang, H.F.[Hai-Feng],
Zhou, Q.[Quan],
Yang, W.Z.[Wen-Zhen],
Wang, Z.F.[Zeng-Fu],
Monocular Depth Estimation Using Information Exchange Network,
ITS(22), No. 6, June 2021, pp. 3491-3503.
IEEE DOI
2106
Estimation, Semantics, Information exchange, Image segmentation,
Convolution, Feature extraction,
semantic information
BibRef
Bian, J.W.[Jia-Wang],
Zhan, H.Y.[Huang-Ying],
Wang, N.Y.[Nai-Yan],
Li, Z.C.[Zhi-Chao],
Zhang, L.[Le],
Shen, C.H.[Chun-Hua],
Cheng, M.M.[Ming-Ming],
Reid, I.D.[Ian D.],
Unsupervised Scale-Consistent Depth Learning from Video,
IJCV(129), No. 9, September 2021, pp. 2548-2564.
Springer DOI
2108
Learn from video input.
BibRef
Song, M.S.[Min-Soo],
Lim, S.[Seokjae],
Kim, W.J.[Won-Jun],
Monocular Depth Estimation Using Laplacian Pyramid-Based Depth
Residuals,
CirSysVideo(31), No. 11, November 2021, pp. 4381-4393.
IEEE DOI
2112
Estimation, Laplace equations, Decoding, Feature extraction,
Convolution, Color, Image reconstruction,
weight standardization
BibRef
Hendra, A.[Andi],
Kanazawa, Y.S.[Yasu-Shi],
Smaller Residual Network for Single Image Depth Estimation,
IEICE(E104-D), No. 11, November 2021, pp. 1992-2001.
WWW Link.
2112
BibRef
Ranftl, R.[René],
Lasinger, K.[Katrin],
Hafner, D.[David],
Schindler, K.[Konrad],
Koltun, V.[Vladlen],
Towards Robust Monocular Depth Estimation:
Mixing Datasets for Zero-Shot Cross-Dataset Transfer,
PAMI(44), No. 3, March 2022, pp. 1623-1637.
IEEE DOI
2202
Training, Estimation, Cameras, Videos, Measurement, Motion pictures,
Monocular depth estimation, single-image depth prediction,
multi-dataset training
BibRef
Labsir, S.[Samy],
Pages, G.[Gaël],
Vivet, D.[Damien],
Lie Group Modelling for an EKF-Based Monocular SLAM Algorithm,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Hu, N.[Nian],
Zhou, H.[Heyu],
Liu, A.A.[An-An],
Huang, X.D.[Xiang-Dong],
Zhang, S.[Shenyuan],
Jin, G.Q.[Guo-Qing],
Guo, J.[Junbo],
Li, X.[Xuanya],
Collaborative Distribution Alignment for 2D image-based 3D shape
retrieval,
JVCIR(83), 2022, pp. 103426.
Elsevier DOI
2202
3D shape retrieval, Cross-domain retrieval, Multi-view learning
BibRef
Jung, D.K.[Dong-Ki],
Choi, J.[Jaehoon],
Lee, Y.[Yonghan],
Kim, D.[Deokhwa],
Kim, C.[Changick],
Manocha, D.[Dinesh],
Lee, D.H.[Dong-Hwan],
DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes,
ICCV21(12777-12787)
IEEE DOI
2203
Training, Tracking, Dynamics, Estimation, Cameras,
3D from a single image and shape-from-x,
Vision for robotics and autonomous vehicles
BibRef
Peluso, V.[Valentino],
Cipolletta, A.[Antonio],
Calimera, A.[Andrea],
Poggi, M.[Matteo],
Tosi, F.[Fabio],
Aleotti, F.[Filippo],
Mattoccia, S.[Stefano],
Monocular Depth Perception on Microcontrollers for Edge Applications,
CirSysVideo(32), No. 3, March 2022, pp. 1524-1536.
IEEE DOI
2203
Estimation, Cameras, Standards, Power demand, Monitoring,
Microcontrollers, Hardware, depth estimation, deep learning,
micro-controllers
BibRef
Chen, S.[Shu],
Pu, Z.D.[Zheng-Dong],
Fan, X.[Xiang],
Zou, B.[Beiji],
Fixing Defect of Photometric Loss for Self-Supervised Monocular Depth
Estimation,
CirSysVideo(32), No. 3, March 2022, pp. 1328-1338.
IEEE DOI
2203
Cameras, Geometry, Estimation, Optical variables control,
Optical imaging, Deep learning, Photometric consistency, epipolar geometry
BibRef
Lu, X.[Xiao],
Sun, H.R.[Hao-Ran],
Wang, X.L.[Xiu-Ling],
Zhang, Z.G.[Zhi-Guo],
Wang, H.X.[Hai-Xia],
Semantically guided self-supervised monocular depth estimation,
IET-IPR(16), No. 5, 2022, pp. 1293-1304.
DOI Link
2203
BibRef
Nie, W.Z.[Wei-Zhi],
Zhao, Y.[Yue],
Nie, J.[Jie],
Liu, A.A.[An-An],
Zhao, S.C.[Si-Cheng],
CLN: Cross-Domain Learning Network for 2D Image-Based 3D Shape
Retrieval,
CirSysVideo(32), No. 3, March 2022, pp. 992-1005.
IEEE DOI
2203
Shape, Feature extraction, Task analysis, Visualization,
Computer architecture, Image processing, information retrieval,
multimedia computing
BibRef
Xiong, M.K.[Ming-Kang],
Zhang, Z.H.[Zheng-Hong],
Zhang, T.[Tao],
Xiong, H.L.[Hui-Lin],
LD-Net: A Lightweight Network for Real-Time Self-Supervised Monocular
Depth Estimation,
SPLetters(29), No. 2022, pp. 882-886.
IEEE DOI
2204
Estimation, Decoding, Convolution, Training, Task analysis,
Computer architecture, Graphics processing units,
lightweight
BibRef
Song, M.S.[Min-Soo],
Kim, W.J.[Won-Jun],
Decomposition and replacement: Spatial knowledge distillation for
monocular depth estimation,
JVCIR(85), 2022, pp. 103523.
Elsevier DOI
2205
Monocular depth estimation, Knowledge distillation,
Laplacian pyramid, ReplaceBlock
BibRef
Zhang, Y.R.[You-Run],
Gong, M.G.[Mao-Guo],
Li, J.Z.[Jian-Zhao],
Zhang, M.Y.[Ming-Yang],
Jiang, F.L.[Fen-Long],
Zhao, H.Y.[Hong-Yu],
Self-Supervised Monocular Depth Estimation With Multiscale Perception,
IP(31), 2022, pp. 3251-3266.
IEEE DOI
2205
Estimation, Optical imaging, Adaptive optics, Training,
Task analysis, Optical variables control,
multiscale optimization
BibRef
Yu, Y.[Ye],
Smith, W.A.P.[William A. P.],
Outdoor Inverse Rendering From a Single Image Using Multiview
Self-Supervision,
PAMI(44), No. 7, July 2022, pp. 3659-3675.
IEEE DOI
2206
Lighting, Rendering (computer graphics), Training, Shape, Estimation,
Geometry, Image decomposition, Inverse rendering,
illumination estimation
BibRef
Ling, C.W.[Chuan-Wu],
Zhang, X.G.[Xiao-Gang],
Chen, H.[Hua],
Unsupervised Monocular Depth Estimation Using Attention and
Multi-Warp Reconstruction,
MultMed(24), 2022, pp. 2938-2949.
IEEE DOI
2206
Estimation, Image reconstruction, Convolution, Task analysis,
Training, Videos, Unsupervised learning, multi-Warp reconstruction
BibRef
Xing, H.[Hao],
Cao, Y.F.[Yi-Fan],
Biber, M.[Maximilian],
Zhou, M.C.[Ming-Chuan],
Burschka, D.[Darius],
Joint prediction of monocular depth and structure using planar and
parallax geometry,
PR(130), 2022, pp. 108806.
Elsevier DOI
2206
Monocular depth estimation, Plane and parallax geometry,
Structure information, Joint prediction model
BibRef
Meng, X.Y.[Xu-Yang],
Fan, C.X.[Chun-Xiao],
Ming, Y.[Yue],
Yu, H.[Hui],
CORNet: Context-Based Ordinal Regression Network for Monocular Depth
Estimation,
CirSysVideo(32), No. 7, July 2022, pp. 4841-4853.
IEEE DOI
2207
Estimation, Image reconstruction, Training, Deep learning, Cameras,
Convergence, Monocular depth estimation, ordinal regression,
spatial attention
BibRef
Wang, L.P.[Lu-Ping],
Wei, H.[Hui],
Curved Alleyway Understanding Based on Monocular Vision in Street
Scenes,
ITS(23), No. 7, July 2022, pp. 8544-8563.
IEEE DOI
2207
Surface reconstruction, Layout, Image edge detection, Cameras,
Image reconstruction, Buildings, Curved alley, scene understanding,
reconstruction
BibRef
Fan, X.N.[Xin-Nan],
Zhou, Z.K.[Zhong-Kai],
Shi, P.F.[Peng-Fei],
Xin, Y.X.[Yuan-Xue],
Zhou, X.[Xuan],
RAFM: Recurrent Atrous Feature Modulation for Accurate Monocular
Depth Estimating,
SPLetters(29), No. , 2022, pp. 1609-1613.
IEEE DOI
2208
BibRef
Earlier: A2, A1, A3, A4, Only:
R-MSFM: Recurrent Multi-Scale Feature Modulation for Monocular Depth
Estimating,
ICCV21(12757-12766)
IEEE DOI
2203
Estimation, Decoding, Feature extraction, Spatial resolution,
Modulation, Convolution, Convolutional codes,
atrous convolution.
Interpolation, Modulation, Estimation, Computer architecture,
Network architecture, Scene analysis and understanding
BibRef
Su, W.[Wen],
Zhang, H.F.[Hai-Feng],
Su, Y.[Yuan],
Yu, J.[Jun],
Wang, Z.F.[Zeng-Fu],
Monocular depth estimation with spatially coherent sliced network,
IVC(124), 2022, pp. 104487.
Elsevier DOI
2208
Depth estimation, Monocular images, Spatial coherence, Sliced depth
BibRef
Lee, S.[Seokju],
Rameau, F.[Francois],
Im, S.H.[Sung-Hoon],
Kweon, I.S.[In So],
Self-Supervised Monocular Depth and Motion Learning in Dynamic Scenes:
Semantic Prior to Rescue,
IJCV(130), No. 9, September 2022, pp. 2265-2285.
Springer DOI
2208
BibRef
Gurram, A.[Akhil],
Tuna, A.F.[Ahmet Faruk],
Shen, F.Y.[Feng-Yi],
Urfalioglu, O.[Onay],
López, A.M.[Antonio M.],
Monocular Depth Estimation Through Virtual-World Supervision and
Real-World SfM Self-Supervision,
ITS(23), No. 8, August 2022, pp. 12738-12751.
IEEE DOI
2208
Training, Estimation, Semantics, Cameras, Laser radar, Optical imaging,
Sensors, Self-supervised monocular depth estimation,
autonomous driving
BibRef
Liu, S.L.[Sheng-Li],
Zhu, X.W.[Xiao-Wen],
Cao, Z.W.[Ze-Wei],
Wang, G.[Gang],
Deep 1D Landmark Representation Learning for Space Target Pose
Estimation,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Poggi, M.[Matteo],
Tosi, F.[Fabio],
Aleotti, F.[Filippo],
Mattoccia, S.[Stefano],
Real-Time Self-Supervised Monocular Depth Estimation Without GPU,
ITS(23), No. 10, October 2022, pp. 17342-17353.
IEEE DOI
2210
BibRef
Earlier: A1, A3, A2, A4:
On the Uncertainty of Self-Supervised Monocular Depth Estimation,
CVPR20(3224-3234)
IEEE DOI
2008
Estimation, Feature extraction, Real-time systems, Hardware,
Decoding, deep learning, deep architectures, unsupervised learning.
Uncertainty, Task analysis, Predictive models, Training, Optical imaging
BibRef
Andraghetti, L.,
Myriokefalitakis, P.,
Dovesi, P.L.,
Luque, B.,
Poggi, M.,
Pieropan, A.,
Mattoccia, S.,
Enhancing Self-Supervised Monocular Depth Estimation with Traditional
Visual Odometry,
3DV19(424-433)
IEEE DOI
1911
Estimation, Training, Cameras,
Visual odometry, Pipelines, Feature extraction,
self supervised
BibRef
Ramirez, P.Z.[Pierluigi Zama],
Poggi, M.[Matteo],
Tosi, F.[Fabio],
Mattoccia, S.[Stefano],
di Stefano, L.[Luigi],
Geometry Meets Semantics for Semi-supervised Monocular Depth Estimation,
ACCV18(III:298-313).
Springer DOI
1906
BibRef
Daimo, R.[Renya],
Ono, S.[Satoshi],
Projection-Based Physical Adversarial Attack for Monocular Depth
Estimation,
IEICE(E106-D), No. 1, January 2023, pp. 31-35.
WWW Link.
2301
BibRef
Wang, Q.[Qi],
Piao, Y.[Yan],
Depth Estimation of Supervised Monocular Images Based on Semantic
Segmentation,
JVCIR(90), 2023, pp. 103753.
Elsevier DOI
2301
Monocular depth estimation, Semantic segmentation,
Shared parameters, Multi-scale feature fusion
BibRef
Li, R.[Runze],
Ji, P.[Pan],
Xu, Y.[Yi],
Bhanu, B.[Bir],
MonoIndoor++: Towards Better Practice of Self-Supervised Monocular
Depth Estimation for Indoor Environments,
CirSysVideo(33), No. 2, February 2023, pp. 830-846.
IEEE DOI
2302
BibRef
Earlier: A2, A1, A4, A3:
MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth
Estimation for Indoor Environments,
ICCV21(12767-12776)
IEEE DOI
2203
Training, Cameras, Pose estimation, Indoor environment, Transformers,
Videos, Monocular depth prediction, self-supervised learning.
Predictive models,
3D from a single image and shape-from-x,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Ehret, T.[Thibaud],
Monocular Depth Estimation: a Review of the 2022 State of the Art,
IPOL(13), 2023, pp. 38-56.
DOI Link
2302
Survey, Monocular Depth.
BibRef
Wang, H.T.[Hao-Tian],
Yang, M.[Meng],
Zhu, C.[Ce],
Zheng, N.N.[Nan-Ning],
RGB-Guided Depth Map Recovery by Two-Stage Coarse-to-Fine Dense CRF
Models,
IP(32), 2023, pp. 1315-1328.
IEEE DOI
2303
Low-pass filters, Laser radar, Task analysis, Sensors, Optimization,
Image sensors, Coarse-to-fine, depth map recovery, dense CRF,
texture-copy artifacts
BibRef
Zhang, A.[Anmei],
Ma, Y.C.[Yun-Chao],
Liu, J.Y.[Jiang-Yu],
Sun, J.[Jian],
Promoting Monocular Depth Estimation by Multi-Scale Residual
Laplacian Pyramid Fusion,
SPLetters(30), 2023, pp. 205-209.
IEEE DOI
2303
Laplace equations, Image resolution, Estimation,
Image reconstruction, Fuses, Refining, Layout, Depth refinement,
multi-scale residual
BibRef
Wang, F.E.[Fu-En],
Yeh, Y.H.[Yu-Hsuan],
Tsai, Y.H.[Yi-Hsuan],
Chiu, W.C.[Wei-Chen],
Sun, M.[Min],
BiFuse++: Self-Supervised and Efficient Bi-Projection Fusion for 360°
Depth Estimation,
PAMI(45), No. 5, May 2023, pp. 5448-5460.
IEEE DOI
2304
BibRef
Earlier: A1, A2, A5, A4, A3:
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion,
CVPR20(459-468)
IEEE DOI
2008
Estimation, Cameras, Training, Sensors, Distortion, Videos,
Neural networks, 360, omnidirectional vision, monocular depth estimation.
Face, Convolution
BibRef
Yin, W.[Wei],
Zhang, J.M.[Jian-Ming],
Wang, O.[Oliver],
Niklaus, S.[Simon],
Chen, S.[Simon],
Liu, Y.[Yifan],
Shen, C.H.[Chun-Hua],
Towards Accurate Reconstruction of 3D Scene Shape From A Single
Monocular Image,
PAMI(45), No. 5, May 2023, pp. 6480-6494.
IEEE DOI
2304
Shape, Point cloud compression,
Estimation, Training, Image reconstruction, Solid modeling,
3D scene shape estimation
BibRef
Ripas, R.[Roger],
Fernandes, L.A.F.[Leandro A.F.],
Improving the planarity and sharpness of monocularly estimated depth
images using the Phong reflection model,
CVIU(233), 2023, pp. 103726.
Elsevier DOI
2307
Monocular depth estimation, Phong reflection model,
Enhanced monocular depth estimation, Importance map
BibRef
Yang, X.H.[Xiang-Hui],
Lin, G.S.[Guo-Sheng],
Zhou, L.P.[Lu-Ping],
Single-View 3D Mesh Reconstruction for Seen and Unseen Categories,
IP(32), 2023, pp. 3746-3758.
IEEE DOI
2307
Image reconstruction, Shape, Generators, Solid modeling,
Feature extraction, Point cloud compression, Mesh,
generalization
BibRef
Chang, R.[Rong],
Yu, K.L.[Kai-Long],
Yang, Y.[Yang],
Self-Supervised Monocular Depth Estimation Using Global and Local
Mixed Multi-Scale Feature Enhancement Network for Low-Altitude UAV
Remote Sensing,
RS(15), No. 13, 2023, pp. 3275.
DOI Link
2307
BibRef
Feng, Y.[Yong],
Chen, J.L.[Jing-Long],
He, S.L.[Shui-Long],
Xu, E.[Enyong],
ABC: Aligning binary centers for single-stage monocular 3D object
detection,
IVC(136), 2023, pp. 104741.
Elsevier DOI
2308
Autonomous driving, Single stage, Monocular detection,
Double heads, Non-maximal suppression (NMS)
BibRef
Tiwari, H.[Hitika],
Kurmi, V.K.[Vinod K.],
Subramanian, V.K.[Venkatesh K.],
Chen, Y.S.[Yong Sheng],
Distilling knowledge for occlusion robust monocular 3D face
reconstruction,
IVC(137), 2023, pp. 104763.
Elsevier DOI
2309
3D face reconstruction, Occlusion robustness, Knowledge distillation,
Duplicate Images Assisted Multi Occlusions Robustification
BibRef
Chen, H.[Hao],
Sun, J.[Jiande],
Zhang, S.X.[Shan-Xin],
Yuan, H.[Hui],
Zhang, H.X.[Hua-Xiang],
Zhang, J.[Jia],
3D pedestrian localization fusing via monocular camera,
JVCIR(95), 2023, pp. 103871.
Elsevier DOI
2309
Monocular camera, Pedestrian localization, Pseudo-LiDAR
BibRef
Papa, L.[Lorenzo],
Russo, P.[Paolo],
Amerini, I.[Irene],
METER: A Mobile Vision Transformer Architecture for Monocular Depth
Estimation,
CirSysVideo(33), No. 10, October 2023, pp. 5882-5893.
IEEE DOI
2310
BibRef
Xue, Y.[Yao],
Cao, Y.[Yu],
Feng, X.B.[Xu-Bin],
Xie, M.[Meilin],
Li, K.[Ke],
Zhang, X.J.[Xing-Jun],
Qian, X.M.[Xue-Ming],
Towards Handling Sudden Changes in Feature Maps During Depth
Estimation,
MultMed(25), 2023, pp. 4002-4012.
IEEE DOI
2310
BibRef
Liang, Y.[Yuan],
Deng, B.[Bailin],
Liu, W.X.[Wen-Xi],
Qin, J.[Jing],
He, S.F.[Sheng-Feng],
Monocular Depth Estimation for Glass Walls With Context: A New
Dataset and Method,
PAMI(45), No. 12, December 2023, pp. 15081-15097.
IEEE DOI
2311
BibRef
Wu, T.[Tong],
Gao, L.[Lin],
Zhang, L.X.[Ling-Xiao],
Lai, Y.K.[Yu-Kun],
Zhang, H.[Hao],
STAR-TM: STructure Aware Reconstruction of Textured Mesh From Single
Image,
PAMI(45), No. 12, December 2023, pp. 15680-15693.
IEEE DOI
2311
BibRef
Yang, L.[Lei],
Zhang, X.Y.[Xin-Yu],
Li, J.[Jun],
Wang, L.[Li],
Zhu, M.[Minghan],
Zhang, C.[Chuang],
Liu, H.P.[Hua-Ping],
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised
Learning Framework for Monocular 3D Object Detection,
CirSysVideo(33), No. 11, November 2023, pp. 6832-6844.
IEEE DOI
2311
BibRef
Li, W.Y.[Wei-Yu],
Chen, X.[Xuelin],
Wang, J.[Jue],
Chen, B.Q.[Bao-Quan],
Patch-Based 3D Natural Scene Generation from a Single Example,
CVPR23(16762-16772)
IEEE DOI
2309
BibRef
Kim, D.[Donggun],
Jang, H.[Hyeonjoong],
Kim, I.[Inchul],
Kim, M.H.[Min H.],
Spatio-Focal Bidirectional Disparity Estimation from a Dual-Pixel
Image,
CVPR23(5023-5032)
IEEE DOI
2309
BibRef
Ahn, B.[Byeongjoo],
de Zeeuw, M.[Michael],
Gkioulekas, I.[Ioannis],
Sankaranarayanan, A.C.[Aswin C.],
Neural Kaleidoscopic Space Sculpting,
CVPR23(4349-4358)
IEEE DOI
2309
BibRef
Wimbauer, F.[Felix],
Yang, N.[Nan],
Rupprecht, C.[Christian],
Cremers, D.[Daniel],
Behind the Scenes: Density Fields for Single View Reconstruction,
CVPR23(9076-9086)
IEEE DOI
2309
BibRef
Melas-Kyriazi, L.[Luke],
Rupprecht, C.[Christian],
Vedaldi, A.[Andrea],
PC2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D
Reconstruction,
CVPR23(12923-12932)
IEEE DOI
2309
BibRef
Izquierdo, S.[Sergio],
Civera, J.[Javier],
SfM-TTR: Using Structure from Motion for Test-Time Refinement of
Single-View Depth Networks,
CVPR23(21466-21476)
IEEE DOI
2309
BibRef
Liu, C.[Ce],
Kumar, S.[Suryansh],
Gu, S.[Shuhang],
Timofte, R.[Radu],
Van Gool, L.J.[Luc J.],
Single Image Depth Prediction Made Better:
A Multivariate Gaussian Take,
CVPR23(17346-17356)
IEEE DOI
2309
BibRef
Tan, T.[Tao],
Dong, Q.[Qiulei],
SMOC-Net: Leveraging Camera Pose for Self-Supervised Monocular Object
Pose Estimation,
CVPR23(21307-21316)
IEEE DOI
2309
BibRef
Chu, T.[Tao],
Zhang, P.[Pan],
Liu, Q.[Qiong],
Wang, J.Q.[Jia-Qi],
BUOL: A Bottom-Up Framework with Occupancy-Aware Lifting for Panoptic
3D Scene Reconstruction From a Single Image,
CVPR23(4937-4946)
IEEE DOI
2309
BibRef
Naumann, A.[Alexander],
Hertlein, F.[Felix],
Dörr, L.[Laura],
Furmans, K.[Kai],
Parcel3D: Shape Reconstruction from Single RGB Images for
Applications in Transportation Logistics,
VISION23(4403-4413)
IEEE DOI
2309
BibRef
Gallagher, L.[Louis],
Sistu, G.[Ganesh],
Horgan, J.[Jonathan],
McDonald, J.B.[John B.],
A System for Dense Monocular Mapping with a Fisheye Camera,
OmniCV23(6479-6487)
IEEE DOI
2309
BibRef
Piccinelli, L.[Luigi],
Sakaridis, C.[Christos],
Yu, F.[Fisher],
iDisc: Internal Discretization for Monocular Depth Estimation,
CVPR23(21477-21487)
IEEE DOI
2309
BibRef
Rajpal, A.[Aakash],
Cheema, N.[Noshaba],
Illgner-Fehns, K.[Klaus],
Slusallek, P.[Philipp],
Jaiswal, S.I.[Sun-Il],
High-Resolution Synthetic RGB-D Datasets for Monocular Depth
Estimation,
NTIRE23(1188-1198)
IEEE DOI
2309
BibRef
Chiavazza, S.[Stefano],
Meyer, S.M.[Svea Marie],
Sandamirskaya, Y.[Yulia],
Low-latency monocular depth estimation using event timing on
neuromorphic hardware,
EventVision23(4071-4080)
IEEE DOI
2309
BibRef
Ning, C.[Chao],
Gan, H.P.[Hong-Ping],
Trap Attention: Monocular Depth Estimation with Manual Traps,
CVPR23(5033-5043)
IEEE DOI
2309
BibRef
Spencer, J.[Jaime],
Qian, C.S.[C. Stella],
Trescakova, M.[Michaela],
Russell, C.[Chris],
Hadfield, S.[Simon],
Graf, E.W.[Erich W.],
Adams, W.J.[Wendy J.],
Schofield, A.J.[Andrew J.],
Elder, J.[James],
Bowden, R.[Richard],
Anwar, A.[Ali],
Chen, H.[Hao],
Chen, X.Z.[Xiao-Zhi],
Cheng, K.[Kai],
Dai, Y.C.[Yu-Chao],
Hoa, H.T.[Huynh Thai],
Hossain, S.[Sadat],
Huang, J.[Jianmian],
Jing, M.[Mohan],
Li, B.[Bo],
Li, C.[Chao],
Li, B.[Baojun],
Liu, Z.W.[Zhi-Wen],
Mattoccia, S.[Stefano],
Mercelis, S.[Siegfried],
Nam, M.[Myungwoo],
Poggi, M.[Matteo],
Qi, X.H.[Xiao-Hua],
Ren, J.[Jiahui],
Tang, Y.[Yang],
Tosi, F.[Fabio],
Trinh, L.[Linh],
Uddin, S.M.N.[S. M. Nadim],
Umair, K.M.[Khan Muhammad],
Wang, K.X.[Kai-Xuan],
Wang, Y.F.[Yu-Fei],
Wang, Y.X.[Yi-Xing],
Xiang, M.[Mochu],
Xu, G.[Guangkai],
Yin, W.[Wei],
Yu, J.[Jun],
Zhang, Q.[Qi],
Zhao, C.Q.[Chao-Qiang],
The Second Monocular Depth Estimation Challenge,
MDEC23(3064-3076)
IEEE DOI
2309
BibRef
Xu, X.M.[Xian-Min],
Lin, Y.X.[Yu-Xin],
Zhou, H.Y.[Hao-Yang],
Zeng, C.[Chong],
Yu, Y.X.[Ya-Xin],
Zhou, K.[Kun],
Wu, H.Z.[Hong-Zhi],
A Unified Spatial-Angular Structured Light for Single-View
Acquisition of Shape and Reflectance,
CVPR23(206-215)
IEEE DOI
2309
BibRef
María-Arribas, D.[David],
Cuesta-Infante, A.[Alfredo],
Pantrigo, J.J.[Juan J.],
The ETS2 Dataset, Synthetic Data from Video Games for Monocular Depth
Estimation,
IbPRIA23(375-386).
Springer DOI
2307
BibRef
Dikov, G.[Georgi],
van Vugt, J.[Joris],
Variational Depth Networks: Uncertainty-aware Monocular Self-supervised
Depth Estimation,
Uncertainty22(43-60).
Springer DOI
2304
BibRef
Tomar, S.S.[Snehal Singh],
Suin, M.[Maitreya],
Rajagopalan, A.N.,
Hybrid Transformer Based Feature Fusion for Self-supervised Monocular
Depth Estimation,
AIM22(308-326).
Springer DOI
2304
BibRef
Shin, U.[Ukcheol],
Park, K.Y.[Kwan-Yong],
Lee, B.U.[Byeong-Uk],
Lee, K.[Kyunghyun],
Kweon, I.S.[In So],
Self-supervised Monocular Depth Estimation from Thermal Images via
Adversarial Multi-spectral Adaptation,
WACV23(5787-5796)
IEEE DOI
2302
Training, Data acquisition, Estimation, Self-supervised learning,
Network architecture, Feature extraction,
Applications: Robotics, 3D computer vision
BibRef
Chen, X.Y.[Xing-Yu],
Li, T.H.[Thomas H.],
Zhang, R.N.[Ruo-Nan],
Li, G.[Ge],
Frequency-Aware Self-Supervised Monocular Depth Estimation,
WACV23(5797-5806)
IEEE DOI
2302
Frequency-domain analysis, Computational modeling,
Image edge detection, Estimation, Low-pass filters,
Low-level and physics-based vision
BibRef
Spencer, J.[Jaime],
Qian, C.S.[C. Stella],
Russell, C.[Chris],
Hadfield, S.[Simon],
Graf, E.[Erich],
Adams, W.[Wendy],
Schofield, A.J.[Andrew J.],
Elder, J.[James],
Bowden, R.[Richard],
Cong, H.[Heng],
Mattoccia, S.[Stefano],
Poggi, M.[Matteo],
Suri, Z.K.[Zeeshan Khan],
Tang, Y.[Yang],
Tosi, F.[Fabio],
Wang, H.[Hao],
Zhang, Y.[Youmin],
Zhang, Y.S.[Yu-Sheng],
Zhao, C.Q.[Chao-Qiang],
The Monocular Depth Estimation Challenge,
MonoDepth23(623-632)
IEEE DOI
2302
Measurement, Interpolation, Conferences, Estimation, Prediction algorithms
BibRef
Auty, D.[Dylan],
Mikolajczyk, K.[Krystian],
Monocular Depth Estimation Using Cues Inspired by Biological Vision
Systems,
ICPR22(4051-4057)
IEEE DOI
2212
Visualization, Machine vision,
Biological system modeling, Semantics, Estimation, Training data
BibRef
Xing, X.X.[Xiao-Xia],
Cai, Y.H.[Ying-Hao],
Lu, T.[Tao],
Yang, Y.P.[Yi-Ping],
Wen, D.Y.[Da-Yong],
Joint Self-Supervised Monocular Depth Estimation and SLAM,
ICPR22(4030-4036)
IEEE DOI
2212
Solid modeling, Simultaneous localization and mapping,
Pose estimation, Feature extraction
BibRef
Patińo, D.[Diego],
Esteves, C.[Carlos],
Daniilidis, K.[Kostas],
Level Set Mesher: Single-image to 3D reconstruction by following the
level sets of the signed distance function,
ICPR22(3994-4000)
IEEE DOI
2212
Manifolds, Geometry, Surface reconstruction, Shape, Level set
BibRef
Zhang, J.Y.[Ji-Yuan],
Tang, L.[Lulu],
Yu, Z.F.[Zhao-Fei],
Lu, J.W.[Ji-Wen],
Huang, T.J.[Tie-Jun],
Spike Transformer: Monocular Depth Estimation for Spiking Camera,
ECCV22(VII:34-52).
Springer DOI
2211
BibRef
Jun, J.[Jinyoung],
Lee, J.H.[Jae-Han],
Lee, C.[Chul],
Kim, C.S.[Chang-Su],
Depth Map Decomposition for Monocular Depth Estimation,
ECCV22(II:18-34).
Springer DOI
2211
BibRef
Chen, M.H.[Ming-Hui],
Zhang, P.P.[Ping-Ping],
Chen, Z.[Zhuo],
Zhang, Y.[Yun],
Wang, X.[Xu],
Kwong, S.[Sam],
End-To-End Depth Map Compression Framework Via Rgb-To-Depth Structure
Priors Learning,
ICIP22(3206-3210)
IEEE DOI
2211
Image coding, Codecs, Fuses, Redundancy, Rate-distortion,
Feature extraction, Data mining, Depth map compression,
feature fusion
BibRef
Lu, J.C.[Jia-Chen],
Zhou, Z.Y.[Zhe-Yuan],
Zhu, X.T.[Xia-Tian],
Xu, H.[Hang],
Zhang, L.[Li],
Learning Ego 3D Representation as Ray Tracing,
ECCV22(XXVI:129-144).
Springer DOI
2211
BibRef
Xing, Z.[Zhen],
Li, H.[Hengduo],
Wu, Z.[Zuxuan],
Jiang, Y.G.[Yu-Gang],
Semi-supervised Single-View 3D Reconstruction via Prototype Shape
Priors,
ECCV22(I:535-551).
Springer DOI
2211
BibRef
Monnier, T.[Tom],
Fisher, M.[Matthew],
Efros, A.A.[Alexei A.],
Aubry, M.[Mathieu],
Share with Thy Neighbors: Single-View Reconstruction by Cross-Instance
Consistency,
ECCV22(I:285-303).
Springer DOI
2211
BibRef
Yu, X.L.[Xuan-Long],
Franchi, G.[Gianni],
Aldea, E.[Emanuel],
On Monocular Depth Estimation and Uncertainty Quantification Using
Classification Approaches for Regression,
ICIP22(1481-1485)
IEEE DOI
2211
Deep learning, Uncertainty, Taxonomy, Estimation, Automobiles,
Depth estimation, Uncertainty Estimation
BibRef
Agarwal, A.[Ashutosh],
Arora, C.[Chetan],
Attention Attention Everywhere:
Monocular Depth Prediction with Skip Attention,
WACV23(5850-5859)
IEEE DOI
2302
Convolutional codes, Image resolution, Fuses, Convolution,
Semantic segmentation, Estimation
BibRef
Agarwal, A.[Ashutosh],
Arora, C.[Chetan],
Depthformer: Multiscale Vision Transformer for Monocular Depth
Estimation with Global Local Information Fusion,
ICIP22(3873-3877)
IEEE DOI
2211
Image coding, Codes, Estimation, Benchmark testing,
Predictive models, Transformers, Task analysis, depth estimation,
adaptive bins
BibRef
Zhou, K.[Kaichen],
Hong, L.[Lanqing],
Chen, C.[Changhao],
Xu, H.[Hang],
Ye, C.Q.[Chao-Qiang],
Hu, Q.Y.[Qing-Yong],
Li, Z.G.[Zhen-Guo],
DevNet:
Self-supervised Monocular Depth Learning via Density Volume Construction,
ECCV22(XXIX:125-142).
Springer DOI
2211
BibRef
Han, W.C.[Wen-Cheng],
Yin, J.[Junbo],
Jin, X.G.[Xiao-Gang],
Dai, X.D.[Xiang-Dong],
Shen, J.B.[Jian-Bing],
BRNet: Exploring Comprehensive Features for Monocular Depth Estimation,
ECCV22(XXXVIII:586-602).
Springer DOI
2211
BibRef
He, M.[Mu],
Hui, L.[Le],
Bian, Y.K.[Yi-Kai],
Ren, J.[Jian],
Xie, J.[Jin],
Yang, J.[Jian],
RA-Depth:
Resolution Adaptive Self-supervised Monocular Depth Estimation,
ECCV22(XXVII:565-581).
Springer DOI
2211
BibRef
Zhang, S.[Sen],
Zhang, J.[Jing],
Tao, D.C.[Da-Cheng],
Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular
Depth Estimation by Integrating IMU Motion Dynamics,
ECCV22(XXXVIII:143-160).
Springer DOI
2211
BibRef
Hornauer, J.[Julia],
Belagiannis, V.[Vasileios],
Gradient-Based Uncertainty for Monocular Depth Estimation,
ECCV22(XX:613-630).
Springer DOI
2211
BibRef
Zhou, Y.[Yunwen],
Kar, A.[Abhishek],
Turner, E.[Eric],
Kowdle, A.[Adarsh],
Guo, C.X.[Chao X.],
DuToit, R.C.[Ryan C.],
Tsotsos, K.[Konstantine],
Learned Monocular Depth Priors in Visual-Inertial Initialization,
ECCV22(XXII:552-570).
Springer DOI
2211
BibRef
Zhou, Z.M.[Zheng-Ming],
Dong, Q.[Qiulei],
Self-distilled Feature Aggregation for Self-supervised Monocular Depth
Estimation,
ECCV22(I:709-726).
Springer DOI
2211
BibRef
Ma, J.Y.[Jing-Yuan],
Lei, X.Y.[Xiang-Yu],
Liu, N.[Nan],
Zhao, X.[Xian],
Pu, S.L.[Shi-Liang],
Towards Comprehensive Representation Enhancement in Semantics-Guided
Self-supervised Monocular Depth Estimation,
ECCV22(I:304-321).
Springer DOI
2211
BibRef
Ren, W.S.[Wei-Song],
Wang, L.J.[Li-Jun],
Piao, Y.[Yongri],
Zhang, M.[Miao],
Lu, H.C.[Hu-Chuan],
Liu, T.[Ting],
Adaptive Co-teaching for Unsupervised Monocular Depth Estimation,
ECCV22(I:89-105).
Springer DOI
2211
BibRef
Xing, Z.[Zhen],
Chen, Y.J.[Yi-Jiang],
Ling, Z.X.[Zhi-Xin],
Zhou, X.D.[Xiang-Dong],
Xiang, Y.[Yu],
Few-Shot Single-View 3D Reconstruction with Memory Prior Contrastive
Network,
ECCV22(I:55-70).
Springer DOI
2211
BibRef
Leung, B.[Brandon],
Ho, C.H.[Chih-Hui],
Vasconcelos, N.M.[Nuno M.],
Black-Box Test-Time Shape REFINEment for Single View 3D
Reconstruction,
L3D-IVU22(4079-4089)
IEEE DOI
2210
Measurement, Systematics, Shape, Pipelines, Benchmark testing,
Reconstruction algorithms
BibRef
Konwer, A.[Aishik],
Xu, X.[Xuan],
Bae, J.[Joseph],
Chen, C.[Chao],
Prasanna, P.[Prateek],
Temporal Context Matters: Enhancing Single Image Prediction with
Disease Progression Representations,
CVPR22(18802-18813)
IEEE DOI
2210
Radiography, Training, Pipelines,
Feature extraction, Transformers, Trajectory, Medical
BibRef
Patakin, N.[Nikolay],
Vorontsova, A.[Anna],
Artemyev, M.[Mikhail],
Konushin, A.[Anton],
Single-Stage 3D Geometry-Preserving Depth Estimation Model Training
on Dataset Mixtures with Uncalibrated Stereo Data,
CVPR22(1695-1704)
IEEE DOI
2210
Training, Point cloud compression, Phase change materials,
Geometry, Solid modeling, Computational modeling,
Scene analysis and understanding
BibRef
Alwala, K.V.[Kalyan Vasudev],
Gupta, A.[Abhinav],
Tulsiani, S.[Shubham],
Pretrain, Self-train, Distill:
A simple recipe for Supersizing 3D Reconstruction,
CVPR22(3763-3772)
IEEE DOI
2210
Training, Solid modeling, Image segmentation, Image recognition,
Shape, Semantics, 3D from single images
BibRef
Walia, A.[Amanpreet],
Walz, S.[Stefanie],
Bijelic, M.[Mario],
Mannan, F.[Fahim],
Julca-Aguilar, F.[Frank],
Langer, M.[Michael],
Ritter, W.[Werner],
Heide, F.[Felix],
Gated2Gated: Self-Supervised Depth Estimation from Gated Images,
CVPR22(2801-2811)
IEEE DOI
2210
Training, Laser radar, Image resolution, Video sequences, Estimation,
Logic gates, Reflection, 3D from single images,
Self- semi- meta- unsupervised learning
BibRef
Benavides, F.T.[Fausto Tapia],
Ignatov, A.[Andrey],
Timofte, R.[Radu],
PhoneDepth: A Dataset for Monocular Depth Estimation on Mobile
Devices,
MobileAI22(3048-3055)
IEEE DOI
2210
Training, Estimation, Cameras, Mobile handsets, Hardware
BibRef
Junayed, M.S.[Masum Shah],
Sadeghzadeh, A.[Arezoo],
Islam, M.B.[Md Baharul],
Wong, L.K.[Lai-Kuan],
Aydin, T.[Tarkan],
HiMODE: A Hybrid Monocular Omnidirectional Depth Estimation Model,
OmniCV22(5208-5217)
IEEE DOI
2210
Visualization, Estimation, Lighting, Computer architecture,
Feature extraction, Transformers
BibRef
Duggal, S.[Shivam],
Pathak, D.[Deepak],
Topologically-Aware Deformation Fields for Single-View 3D
Reconstruction,
CVPR22(1526-1536)
IEEE DOI
2210
Shape, Rendering (computer graphics), Pattern recognition,
Image reconstruction, Strain, 3D from single images, Vision + graphics
BibRef
Swami, K.[Kunal],
Muduli, A.[Amrit],
Gurram, U.[Uttam],
Bajpai, P.[Pankaj],
Do What You Can, With What You Have: Scale-aware and High Quality
Monocular Depth Estimation Without Real World Labels,
NTIRE22(987-996)
IEEE DOI
2210
Training, Geometry, Semantics, Estimation, Training data,
Benchmark testing, Task analysis
BibRef
Gümeli, C.[Can],
Dai, A.[Angela],
Nießner, M.[Matthias],
ROCA: Robust CAD Model Retrieval and Alignment from a Single Image,
CVPR22(4012-4021)
IEEE DOI
2210
Image sensors, Solid modeling, Image analysis, Shape, Databases,
Mixed reality, 3D from single images,
Vision + graphics
BibRef
Yuan, W.H.[Wei-Hao],
Gu, X.D.[Xiao-Dong],
Dai, Z.Z.[Zuo-Zhuo],
Zhu, S.[Siyu],
Tan, P.[Ping],
Neural Window Fully-connected CRFs for Monocular Depth Estimation,
CVPR22(3906-3915)
IEEE DOI
2210
Measurement, Estimation, Transformers, Pattern recognition, Decoding,
Computational complexity, 3D from single images,
Robot vision
BibRef
Li, Y.Y.[Yu-Yan],
Guo, Y.L.[Yu-Liang],
Yan, Z.X.[Zhi-Xin],
Huang, X.Y.[Xin-Yu],
Duan, Y.[Ye],
Ren, L.[Liu],
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion,
CVPR22(2791-2800)
IEEE DOI
2210
Scalability, Pipelines, Estimation, Transforms, Distortion,
Transformers, 3D from single images, RGBD sensors and analytics,
Scene analysis and understanding
BibRef
Rey-Area, M.[Manuel],
Yuan, M.Z.[Ming-Ze],
Richardt, C.[Christian],
360MonoDepth: High-Resolution 360° Monocular Depth Estimation,
CVPR22(3752-3762)
IEEE DOI
2210
Image resolution, Codes, Estimation, Graphics processing units,
Virtual reality, 3D from single images
BibRef
Wen, X.[Xin],
Zhou, J.S.[Jun-Sheng],
Liu, Y.S.[Yu-Shen],
Su, H.[Hua],
Dong, Z.[Zhen],
Han, Z.Z.[Zhi-Zhong],
3D Shape Reconstruction from 2D Images with Disentangled Attribute
Flow,
CVPR22(3793-3803)
IEEE DOI
2210
Training, Shape, Semantics, Sensor phenomena and characterization,
Reconstruction algorithms, Pattern recognition,
3D from multi-view and sensors
BibRef
Patil, V.[Vaishakh],
Sakaridis, C.[Christos],
Liniger, A.[Alexander],
Van Gool, L.J.[Luc J.],
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior,
CVPR22(1600-1611)
IEEE DOI
2210
Training, Codes, Estimation, Computer architecture,
Benchmark testing, 3D from single images, Scene analysis and understanding
BibRef
Zhao, Z.[Zimeng],
Zuo, B.H.[Bing-Hui],
Xie, W.[Wei],
Wang, Y.G.[Yan-Gang],
Stability-driven Contact Reconstruction From Monocular Color Images,
CVPR22(1633-1643)
IEEE DOI
2210
Shape, Stability criteria, Pipelines, Pattern recognition,
Image reconstruction, Physics, 3D from single images,
Self- semi- meta- unsupervised learning
BibRef
Petrovai, A.[Andra],
Nedevschi, S.[Sergiu],
Exploiting Pseudo Labels in a Self-Supervised Learning Framework for
Improved Monocular Depth Estimation,
CVPR22(1568-1578)
IEEE DOI
2210
Training, Solid modeling, Image resolution, Filtering,
Pose estimation, Self-supervised learning, 3D from single images,
Self- semi- meta- unsupervised learning
BibRef
Zohaib, M.[Mohammad],
Taiana, M.[Matteo],
Padalkar, M.G.[Milind Gajanan],
del Bue, A.[Alessio],
3D Key-Points Estimation from Single-View RGB Images,
CIAP22(II:27-38).
Springer DOI
2205
BibRef
Chen, Z.[Zhi],
Ye, X.Q.[Xiao-Qing],
Yang, W.[Wei],
Xu, Z.B.[Zhen-Bo],
Tan, X.[Xiao],
Zou, Z.K.[Zhi-Kang],
Ding, E.[Errui],
Zhang, X.M.[Xin-Ming],
Huang, L.S.[Liu-Sheng],
Revealing the Reciprocal Relations between Self-Supervised Stereo and
Monocular Depth Estimation,
ICCV21(15509-15518)
IEEE DOI
2203
Computer network reliability, Estimation, Collaboration,
Benchmark testing, Reliability engineering, Task analysis,
3D from multiview and other sensors
BibRef
Choi, H.[Hyesong],
Lee, H.[Hunsang],
Kim, S.[Sunkyung],
Kim, S.[Sunok],
Kim, S.[Seungryong],
Sohn, K.H.[Kwang-Hoon],
Min, D.B.[Dong-Bo],
Adaptive confidence thresholding for monocular depth estimation,
ICCV21(12788-12798)
IEEE DOI
2203
Uncertainty, Convolution, Estimation, Probabilistic logic,
Picture archiving and communication systems,
Vision for robotics and autonomous vehicles
BibRef
Peng, R.[Rui],
Wang, R.G.[Rong-Gang],
Lai, Y.W.[Ya-Wen],
Tang, L.Y.[Lu-Yang],
Cai, Y.G.[Yan-Gang],
Excavating the Potential Capacity of Self-Supervised Monocular Depth
Estimation,
ICCV21(15540-15549)
IEEE DOI
2203
Costs, Codes, Computational modeling, Semantics, Estimation,
Data models, Scene analysis and understanding, Stereo,
Vision for robotics and autonomous vehicles
BibRef
Kuo, W.C.[Wei-Cheng],
Angelova, A.[Anelia],
Lin, T.Y.[Tsung-Yi],
Dai, A.[Angela],
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape
Retrieval from a Single Image,
ICCV21(12569-12579)
IEEE DOI
2203
Geometry, Solid modeling, Shape, Databases, Grounding,
3D from a single image and shape-from-x,
Scene analysis and understanding
BibRef
Naderi, T.[Taher],
Sadovnik, A.[Amir],
Hayward, J.[Jason],
Qi, H.R.[Hai-Rong],
Monocular Depth Estimation with Adaptive Geometric Attention,
WACV22(617-627)
IEEE DOI
2202
Adaptation models, Solid modeling, Image edge detection,
Vision for Robotics
BibRef
Lee, M.[Minhyeok],
Hwang, S.[Sangwon],
Park, C.[Chaewon],
Lee, S.Y.[Sang-Youn],
EdgeConv with Attention Module for Monocular Depth Estimation,
WACV22(2364-2373)
IEEE DOI
2202
Convolution, Image edge detection, Estimation, Lighting, Predictive models,
Vision for Robotics
BibRef
Cardace, A.[Adriano],
de Luigi, L.[Luca],
Ramirez, P.Z.[Pierluigi Zama],
Salti, S.[Samuele],
di Stefano, L.[Luigi],
Plugging Self-Supervised Monocular Depth into Unsupervised Domain
Adaptation for Semantic Segmentation,
WACV22(1999-2009)
IEEE DOI
2202
Training, Image segmentation, Adaptation models,
Roads, Semantics, Estimation, Transfer, Few-shot, Grouping and Shape
BibRef
Sagar, A.[Abhinav],
Monocular Depth Estimation Using Multi Scale Neural Network And
Feature Fusion,
Hazards22(656-662)
IEEE DOI
2202
Training, Measurement, Convolution, Estimation, Network architecture
BibRef
Postels, J.[Janis],
Liu, M.Y.[Meng-Ya],
Spezialetti, R.[Riccardo],
Van Gool, L.J.[Luc J.],
Tombari, F.[Federico],
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud
Generation and Reconstruction,
3DV21(1249-1258)
IEEE DOI
2201
Point cloud compression, Geometry, Training, Solid modeling,
Interpolation, Runtime, Generative Models, Normalizing Flows,
Single View Reconstruction
BibRef
Ruhkamp, P.[Patrick],
Gao, D.[Daoyi],
Chen, H.Z.[Han-Zhi],
Navab, N.[Nassir],
Busam, B.[Beniamin],
Attention meets Geometry: Geometry Guided Spatial-Temporal Attention
for Consistent Self-Supervised Monocular Depth Estimation,
3DV21(837-847)
IEEE DOI
2201
Geometry, Measurement, Aggregates, Pipelines, Estimation, Predictive models
BibRef
Persson, P.[Patrik],
Öström, L.[Linn],
Olsson, C.[Carl],
Ĺström, K.[Kalle],
Parameterization of Ambiguity in Monocular Depth Prediction,
3DV21(761-770)
IEEE DOI
2201
Geometry, Training, Measurement, Image recognition, Neural networks,
Estimation, 3D Reconstruction, Monocular Depth Parameterization,
Machine Learning
BibRef
Hirose, N.[Noriaki],
Taguchi, S.[Shun],
Kawano, K.[Keisuke],
Koide, S.[Satoshi],
Variational Monocular Depth Estimation for Reliability Prediction,
3DV21(637-647)
IEEE DOI
2201
Training, Solid modeling, Uncertainty, Supervised learning,
Estimation, Reliability theory, depth estimation,
self supervised learning
BibRef
Li, Y.Y.[Yu-Yan],
Yan, Z.X.[Zhi-Xin],
Duan, Y.[Ye],
Ren, L.[Liu],
PanoDepth:
A Two-Stage Approach for Monocular Omnidirectional Depth Estimation,
3DV21(648-658)
IEEE DOI
2201
Geometry, Solid modeling, Codes, Pipelines, Estimation, Virtual reality
BibRef
Yan, J.X.[Jia-Xing],
Zhao, H.[Hong],
Bu, P.H.[Peng-Hui],
Jin, Y.S.[Yu-Sheng],
Channel-Wise Attention-Based Network for Self-Supervised Monocular
Depth Estimation,
3DV21(464-473)
IEEE DOI
2201
Fuses, Aggregates, Estimation, Channel estimation, Predictive models,
Benchmark testing
BibRef
Takmaz, A.[Ayça],
Paudel, D.P.[Danda Pani],
Probst, T.[Thomas],
Chhatkuli, A.[Ajad],
Oswald, M.R.[Martin R.],
Van Gool, L.J.[Luc J.],
Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes,
3DV21(825-836)
IEEE DOI
2201
Training, Motion segmentation, Dynamics, Pipelines, Neural networks,
Estimation, non-rigid reconstruction, 3d reconstruction, unsupervised
BibRef
Zhou, Y.[Yefan],
Shen, Y.[Yiru],
Yan, Y.J.[Yu-Jun],
Feng, C.[Chen],
Yang, Y.Q.[Yao-Qing],
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition
in Single-View 3D Reconstruction Networks,
3DV21(1331-1340)
IEEE DOI
2201
Training, Image recognition, Systematics, Shape, Training data,
Artificial neural networks, Single view 3D reconstruction,
Reconstruction metric
BibRef
Chen, X.Y.[Xing-Yu],
Zhang, R.N.[Ruo-Nan],
Jiang, J.[Ji],
Wang, Y.[Yan],
Li, G.[Ge],
Li, T.H.[Thomas H.],
Self-Supervised Monocular Depth Estimation: Solving the
Edge-Fattening Problem,
WACV23(5765-5775)
IEEE DOI
2302
Measurement, Computational modeling, Estimation, Optimization,
Algorithms: 3D computer vision, Low-level and physics-based vision
BibRef
Li, K.[Keyao],
Li, G.[Ge],
Li, T.H.[Thomas H.],
Rethinking Training Objective for Self-Supervised Monocular Depth
Estimation: Semantic Cues To Rescue,
ICIP21(3308-3312)
IEEE DOI
2201
Training, Integrated optics, Solid modeling, Semantics, Estimation,
Optical variables control, self-supervised learning, semantic cues
BibRef
Jiang, C.W.[Chen-Weinan],
Liu, H.C.[Hai-Chun],
Li, L.Z.[Lan-Zhen],
Pan, C.C.[Chang-Chun],
Attention-Based Self-Supervised Learning Monocular Depth Estimation
With Edge Refinement,
ICIP21(3218-3222)
IEEE DOI
2201
Image edge detection, Neural networks, Brightness, Estimation,
Feature extraction, Videos, self-supervised learning, monocular,
edge refinement
BibRef
Victor, A.C.[Ankita Christine],
Sreevalsan-Nair, J.[Jaya],
Building 3D Virtual Worlds from Monocular Images of Urban Road Traffic
Scenes,
ISVC21(II:461-474).
Springer DOI
2112
BibRef
Laradji, I.[Issam],
Rodríguez, P.[Pau],
Vazquez, D.[David],
Nowrouzezahrai, D.[Derek],
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D
Reconstruction,
Diff3D21(1427-1436)
IEEE DOI
2112
Training, Codes, Estimation, Entropy
BibRef
Ramamonjisoa, M.[Michaël],
Firman, M.[Michael],
Watson, J.[Jamie],
Lepetit, V.[Vincent],
Turmukhambetov, D.[Daniyar],
Single Image Depth Prediction with Wavelet Decomposition,
CVPR21(11084-11093)
IEEE DOI
2111
Analytical models, Neural networks, Estimation,
Computer architecture, Wavelet analysis, Decoding, Pattern recognition
BibRef
Wang, Y.Z.[Yi-Zhi],
Huang, Z.[Zeyu],
Shamir, A.[Ariel],
Huang, H.[Hui],
Zhang, H.[Hao],
Hu, R.Z.[Rui-Zhen],
ARO-Net: Learning Implicit Fields from Anchored Radial Observations,
CVPR23(3572-3581)
IEEE DOI
2309
BibRef
Li, M.Y.[Man-Yi],
Zhang, H.[Hao],
D2IM-Net: Learning Detail Disentangled Implicit Fields from Single
Images,
CVPR21(10241-10250)
IEEE DOI
2111
Surface reconstruction,
Laplace equations, Shape, Decoding, Pattern recognition
BibRef
Bechtold, J.[Jan],
Tatarchenko, M.[Maxim],
Fischer, V.[Volker],
Brox, T.[Thomas],
Fostering Generalization in Single-view 3D Reconstruction by Learning
a Hierarchy of Local and Global Shape Priors,
CVPR21(15875-15884)
IEEE DOI
2111
Training, Shape, Training data, Computer architecture, Network architecture
BibRef
Kluger, F.[Florian],
Ackermann, H.[Hanno],
Brachmann, E.[Eric],
Yang, M.Y.[Michael Ying],
Rosenhahn, B.[Bodo],
Cuboids Revisited: Learning Robust 3D Shape Fitting to Single RGB
Images,
CVPR21(13065-13074)
IEEE DOI
2111
Training, Measurement, Shape, Annotations, Fitting, Neural networks
BibRef
Lienen, J.[Julian],
Hüllermeier, E.[Eyke],
Ewerth, R.[Ralph],
Nommensen, N.[Nils],
Monocular Depth Estimation via Listwise Ranking using the
Plackett-Luce Model,
CVPR21(14590-14599)
IEEE DOI
2111
Training, Neural networks, Estimation, Training data,
Predictive models, Data models, Probability distribution
BibRef
Yang, Z.P.[Zhen-Pei],
Li, L.E.[Li Erran],
Huang, Q.X.[Qi-Xing],
StruMonoNet: Structure-Aware Monocular 3D Prediction,
CVPR21(7409-7418)
IEEE DOI
2111
Visualization, Boosting, Pattern recognition
BibRef
Miangoleh, S.M.H.[S. Mahdi H.],
Dille, S.[Sebastian],
Mai, L.[Long],
Paris, S.[Sylvain],
Aksoy, Y.[Yagiz],
Boosting Monocular Depth Estimation Models to High-Resolution via
Content-Adaptive Multi-Resolution Merging,
CVPR21(9680-9689)
IEEE DOI
2111
Location awareness, Image segmentation,
Image resolution, Merging, Neural networks, Estimation
BibRef
Watson, J.[Jamie],
Aodha, O.M.[Oisin Mac],
Prisacariu, V.[Victor],
Brostow, G.[Gabriel],
Firman, M.[Michael],
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth,
CVPR21(1164-1174)
IEEE DOI
2111
Training, Costs, Adaptive systems,
Computational modeling, Estimation, Cameras
BibRef
Weng, Z.Z.[Zhen-Zhen],
Yeung, S.[Serena],
Holistic 3D Human and Scene Mesh Estimation from Single View Images,
CVPR21(334-343)
IEEE DOI
2111
Measurement, Solid modeling, Computational modeling, Pose estimation
BibRef
Yin, W.[Wei],
Zhang, J.M.[Jian-Ming],
Wang, O.[Oliver],
Niklaus, S.[Simon],
Mai, L.[Long],
Chen, S.[Simon],
Shen, C.H.[Chun-Hua],
Learning to Recover 3D Scene Shape from a Single Image,
CVPR21(204-213)
IEEE DOI
2111
Training, Geometry, Shape, Estimation,
Reconstruction algorithms, Predictive models
BibRef
Hu, T.[Tao],
Wang, L.W.[Li-Wei],
Xu, X.G.[Xiao-Gang],
Liu, S.[Shu],
Jia, J.Y.[Jia-Ya],
Self-Supervised 3D Mesh Reconstruction from Single Images,
CVPR21(5998-6007)
IEEE DOI
2111
Solid modeling, Annotations, Shape,
Motorcycles, Reconstruction algorithms, Pattern recognition
BibRef
Buquet, J.[Julie],
Zhang, J.S.[Jin-Song],
Roulet, P.[Patrice],
Thibault, S.[Simon],
Lalonde, J.F.[Jean-François],
Evaluating the Impact of Wide-Angle Lens Distortion on Learning-based
Depth Estimation,
OmniCV21(3688-3696)
IEEE DOI
2109
Training, Nonlinear distortion, Neural networks,
Estimation, Tools, Cameras
BibRef
Wang, Y.R.[Yi-Ran],
Li, X.Y.[Xing-Yi],
Shi, M.[Min],
Xian, K.[Ke],
Cao, Z.G.[Zhi-Guo],
Knowledge Distillation for Fast and Accurate Monocular Depth
Estimation on Mobile Devices,
MAI21(2457-2465)
IEEE DOI
2109
Knowledge engineering, Performance evaluation, Training,
Visualization, Neural networks, Estimation
BibRef
Yücel, M.K.[Mehmet Kerim],
Dimaridou, V.[Valia],
Drosou, A.[Anastasios],
Saŕ-Garriga, A.[Albert],
Real-time Monocular Depth Estimation with Sparse Supervision on
Mobile,
MAI21(2428-2437)
IEEE DOI
2109
Runtime, Computational modeling, Graphics processing units,
Estimation, Predictive models, Mobile handsets, Real-time systems
BibRef
Ignatov, A.[Andrey],
Malivenko, G.[Grigory],
Timofte, R.[Radu],
Treszczotko, L.[Lukasz],
Chang, X.[Xin],
Ksiazek, P.[Piotr],
Lopuszynski, M.[Michal],
Pioro, M.[Maciej],
Rudnicki, R.[Rafal],
Smyl, M.[Maciej],
Ma, Y.J.[Yu-Jie],
Li, Z.Y.[Zhen-Yu],
Chen, Z.[Zehui],
Xu, J.[Jialei],
Liu, X.M.[Xian-Ming],
Jiang, J.J.[Jun-Jun],
Shi, X.[XueChao],
Xu, D.[Difan],
Li, Y.[Yanan],
Wang, X.T.[Xiao-Tao],
Lei, L.[Lei],
Zhang, Z.[Ziyu],
Wang, Y.C.[Yi-Cheng],
Huang, Z.L.[Zi-Long],
Luo, G.Z.[Guo-Zhong],
Yu, G.[Gang],
Fu, B.[Bin],
Li, J.Q.[Jia-Qi],
Wang, Y.[Yiran],
Huang, Z.[Zihao],
Cao, Z.G.[Zhi-Guo],
Conde, M.V.[Marcos V.],
Sapozhnikov, D.[Denis],
Lee, B.H.[Byeong Hyun],
Park, D.[Dongwon],
Hong, S.[Seongmin],
Lee, J.H.[Joon-Hee],
Lee, S.[Seunggyu],
Chun, S.Y.[Se Young],
Efficient Single-image Depth Estimation on Mobile Devices, Mobile Ai &
Aim 2022 Challenge: Report,
AIM22(71-91).
Springer DOI
2304
BibRef
Ignatov, A.[Andrey],
Malivenko, G.[Grigory],
Plowman, D.[David],
Shukla, S.[Samarth],
Timofte, R.[Radu],
Zhang, Z.Y.[Zi-Yu],
Wang, Y.C.[Yi-Cheng],
Huang, Z.L.[Zi-Long],
Luo, G.Z.[Guo-Zhong],
Yu, G.[Gang],
Fu, B.[Bin],
Wang, Y.R.[Yi-Ran],
Li, X.Y.[Xing-Yi],
Shi, M.[Min],
Xian, K.[Ke],
Cao, Z.G.[Zhi-Guo],
Du, J.H.[Jin-Hua],
Wu, P.L.[Pei-Lin],
Ge, C.[Chao],
Yao, J.Y.[Jiao-Yang],
Tu, F.[Fangwen],
Li, B.[Bo],
Yoo, J.E.[Jung Eun],
Seo, K.[Kwanggyoon],
Xu, J.[Jialei],
Li, Z.Y.[Zhen-Yu],
Liu, X.M.[Xian-Ming],
Jiang, J.J.[Jun-Jun],
Chen, W.C.[Wei-Chi],
Joya, S.[Shayan],
Fan, H.H.[Huan-Huan],
Kang, Z.[Zhaobing],
Li, A.[Ang],
Feng, T.P.[Tian-Peng],
Liu, Y.[Yang],
Sheng, C.N.[Chuan-Nan],
Yin, J.[Jian],
Benavides, F.T.[Fausto T.],
Fast and Accurate Single-Image Depth Estimation on Mobile Devices,
Mobile AI 2021 Challenge: Report,
MAI21(2545-2557)
IEEE DOI
2109
Meters, Image resolution, Estimation,
Real-time systems, Pattern recognition
BibRef
Leroy, R.,
Trouvé-Peloux, P.,
Champagnat, F.,
Le Saux, B.,
Carvalho, M.,
Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal
Transport,
MVA21(1-5)
DOI Link
2109
Training, Measurement,
Neural networks, Estimation, Prediction methods
BibRef
Chen, Z.W.[Zi-Wen],
Guo, Z.X.[Zi-Xuan],
Weinman, J.[Jerod],
Improved Point Transformation Methods For Self-Supervised Depth
Prediction,
CRV21(111-118)
IEEE DOI
2108
Learn using stereo pairs.
Training, Machine learning algorithms, Estimation,
Machine learning, Predictive models, Network architecture,
neural networks
BibRef
Saeedan, F.[Faraz],
Roth, S.[Stefan],
Boosting Monocular Depth with Panoptic Segmentation Maps,
WACV21(3852-3861)
IEEE DOI
2106
Training, Image segmentation, Smoothing methods,
Semantics, Estimation
BibRef
Kuznietsov, Y.[Yevhen],
Proesmans, M.[Marc],
Van Gool, L.J.[Luc J.],
CoMoDA: Continuous Monocular Depth Adaptation Using Past Experiences,
WACV21(2906-2916)
IEEE DOI
2106
Training, Adaptation models, Optical buffering, Pipelines,
Estimation, Optimized production technology, Streaming media
BibRef
Lu, Y.W.[Ya-Wen],
Lu, G.Y.[Guo-Yu],
An Alternative of LiDAR in Nighttime:
Unsupervised Depth Estimation Based on Single Thermal Image,
WACV21(3832-3842)
IEEE DOI
2106
Image sensors, Laser radar, Image resolution, Image color analysis,
Lasers, Estimation, Lighting
BibRef
Domnik, M.[Matthias],
Proenca, P.[Pedro],
Delaune, J.[Jeff],
Thiem, J.[Jörg],
Brockers, R.[Roland],
Dense 3D-Reconstruction from Monocular Image Sequences for
Computationally Constrained UAS*,
WACV21(1819-1827)
IEEE DOI
2106
Structure from motion,
Computational modeling, Cameras, Real-time systems, Hardware, Computational efficiency
BibRef
Phan, M.H.[Minh Hieu],
Phung, S.L.[Son Lam],
Bouzerdoum, A.[Abdesselam],
Ordinal Depth Classification Using Region-based Self-attention,
ICPR21(3620-3627)
IEEE DOI
2105
Estimation, Channel estimation, Feature extraction,
Classification algorithms, Reliability, Task analysis
BibRef
Kim, D.[Doyeon],
Joo, D.G.[Dong-Gyu],
Kim, J.[Junmo],
Delivering Meaningful Representation for Monocular Depth Estimation,
ICPR21(7790-7795)
IEEE DOI
2105
Image analysis, Fuses, Estimation,
Network architecture, Performance gain, Feature extraction
BibRef
Li, Z.[Zhi],
Zhu, X.Y.[Xiao-Yang],
Yu, H.T.[Hai-Tao],
Zhang, Q.[Qi],
Jiang, Y.[Yongshi],
Edge-Aware Monocular Dense Depth Estimation with Morphology,
ICPR21(2935-2942)
IEEE DOI
2105
Simultaneous localization and mapping, Image edge detection
BibRef
Irie, G.[Go],
Ikami, D.[Daiki],
Kawanishi, T.[Takahito],
Kashino, K.[Kunio],
Cascaded Transposed Long-range Convolutions for Monocular Depth
Estimation,
ACCV20(III:437-453).
Springer DOI
2103
BibRef
Peng, K.S.[Kuo-Shiuan],
Ditzler, G.[Gregory],
Rozenblit, J.[Jerzy],
A Light-weight Monocular Depth Estimation with Edge-guided Occlusion
Fading Reduction,
ISVC20(II:69-81).
Springer DOI
2103
BibRef
Wang, Y.,
Luo, L.,
Shen, X.,
Mei, X.,
DynOcc: Learning Single-View Depth from Dynamic Occlusion Cues,
3DV20(514-523)
IEEE DOI
2102
Videos, Estimation, Image edge detection,
Training, Optical imaging, Reliability
BibRef
Du, D.,
Zhang, Z.,
Han, X.,
Cui, S.,
Liu, L.,
VIPNet: A Fast and Accurate Single-View Volumetric Reconstruction by
Learning Sparse Implicit Point Guidance,
3DV20(553-562)
IEEE DOI
2102
Shape, Image reconstruction, Topology,
Network topology, Decoding, hybrid shape learning
BibRef
Li, H.,
Ye, W.,
Zhang, G.,
Zhang, S.,
Bao, H.,
Saliency Guided Subdivision for Single-View Mesh Reconstruction,
3DV20(1098-1107)
IEEE DOI
2102
Strain, Faces, Shape,
Surface reconstruction, Memory management, Feature extraction
BibRef
Han, Z.Z.[Zhi-Zhong],
Qiao, G.H.[Guan-Hui],
Liu, Y.S.[Yu-Shen],
Zwicker, M.[Matthias],
SeqXY2SeqZ: Structure Learning for 3d Shapes by Sequentially Predicting
1D Occupancy Segments from 2d Coordinates,
ECCV20(XXIV:607-625).
Springer DOI
2012
BibRef
Badger, M.[Marc],
Wang, Y.[Yufu],
Modh, A.[Adarsh],
Perkes, A.[Ammon],
Kolotouros, N.[Nikos],
Pfrommer, B.G.[Bernd G.],
Schmidt, M.F.[Marc F.],
Daniilidis, K.[Kostas],
3d Bird Reconstruction: A Dataset, Model, and Shape Recovery from a
Single View,
ECCV20(XVIII:1-17).
Springer DOI
2012
BibRef
Wang, J.R.[Jian-Ren],
Fang, Z.Y.[Zhao-Yuan],
GSIR: Generalizable 3d Shape Interpretation and Reconstruction,
ECCV20(XIII:498-514).
Springer DOI
2011
Jointly learn 3D shape interpretation and reconstruction.
BibRef
Tiwari, L.[Lokender],
Ji, P.[Pan],
Tran, Q.H.[Quoc-Huy],
Zhuang, B.B.[Bing-Bing],
Anand, S.[Saket],
Chandraker, M.[Manmohan],
Pseudo RGB-D for Self-improving Monocular SLAM and Depth Prediction,
ECCV20(XI:437-455).
Springer DOI
2011
BibRef
Michalkiewicz, M.[Mateusz],
Parisot, S.[Sarah],
Tsogkas, S.[Stavros],
Baktashmotlagh, M.[Mahsa],
Eriksson, A.[Anders],
Belilovsky, E.[Eugene],
Few-shot Single-view 3-d Object Reconstruction with Compositional
Priors,
ECCV20(XXV:614-630).
Springer DOI
2011
BibRef
Goel, S.[Shubham],
Kanazawa, A.[Angjoo],
Malik, J.[Jitendra],
Shape and Viewpoint Without Keypoints,
ECCV20(XV:88-104).
Springer DOI
2011
BibRef
Denninger, M.[Maximilian],
Triebel, R.[Rudolph],
3d Scene Reconstruction from a Single Viewport,
ECCV20(XXII:51-67).
Springer DOI
2011
BibRef
Wang, Z.,
Isler, V.,
Lee, D.D.,
Surface Hof: Surface Reconstruction From A Single Image Using Higher
Order Function Networks,
ICIP20(2666-2670)
IEEE DOI
2011
Surface reconstruction,
Image reconstruction, Surface treatment, Decoding, Task analysis,
Computer Graphics
BibRef
Chen, T.[Tian],
An, S.J.[Shi-Jie],
Zhang, Y.[Yuan],
Ma, C.Y.[Chong-Yang],
Wang, H.Y.[Hua-Yan],
Guo, X.Y.[Xiao-Yan],
Zheng, W.[Wen],
Improving Monocular Depth Estimation by Leveraging Structural Awareness
and Complementary Datasets,
ECCV20(XIV:90-108).
Springer DOI
2011
BibRef
Huynh, L.[Lam],
Nguyen-Ha, P.[Phong],
Matas, J.G.[Jiri G.],
Rahtu, E.[Esa],
Heikkilä, J.[Janne],
Guiding Monocular Depth Estimation Using Depth-attention Volume,
ECCV20(XXVI:581-597).
Springer DOI
2011
BibRef
Li, X.T.[Xue-Ting],
Liu, S.F.[Si-Fei],
Kim, K.H.[Ki-Hwan],
de Mello, S.[Shalini],
Jampani, V.[Varun],
Yang, M.H.[Ming-Hsuan],
Kautz, J.[Jan],
Self-supervised Single-view 3d Reconstruction via Semantic Consistency,
ECCV20(XIV:677-693).
Springer DOI
2011
BibRef
Klingner, M.[Marvin],
Termöhlen, J.A.[Jan-Aike],
Mikolajczyk, J.[Jonas],
Fingscheidt, T.[Tim],
Self-supervised Monocular Depth Estimation: Solving the Dynamic Object
Problem by Semantic Guidance,
ECCV20(XX:582-600).
Springer DOI
2011
BibRef
Kniaz, V.V.[Vladimir V.],
Knyaz, V.A.[Vladimir A.],
Remondino, F.[Fabio],
Bordodymov, A.[Artem],
Moshkantsev, P.[Petr],
Image-to-voxel Model Translation for 3d Scene Reconstruction and
Segmentation,
ECCV20(VII:105-124).
Springer DOI
2011
BibRef
Li, Y.C.[Yi-Chen],
Mo, K.C.[Kai-Chun],
Shao, L.[Lin],
Sung, M.[Minhyuk],
Guibas, L.J.[Leonidas J.],
Learning 3d Part Assembly from a Single Image,
ECCV20(VI:664-682).
Springer DOI
2011
BibRef
Wang, L.J.[Li-Jun],
Zhang, J.M.[Jian-Ming],
Wang, Y.F.[Yi-Fan],
Lu, H.C.[Hu-Chuan],
Ruan, X.[Xiang],
Cliffnet for Monocular Depth Estimation with Hierarchical Embedding
Loss,
ECCV20(V:316-331).
Springer DOI
2011
BibRef
Hampali, S.[Shreyas],
Stekovic, S.[Sinisa],
Sarkar, S.D.[Sayan Deb],
Kumar, C.S.[Chetan S.],
Fraundorfer, F.[Friedrich],
Lepetit, V.[Vincent],
Monte Carlo Scene Search for 3D Scene Understanding,
CVPR21(13799-13808)
IEEE DOI
2111
Monte Carlo methods, Layout,
Training data, Search problems, Rendering (computer graphics), Space exploration
BibRef
Stekovic, S.[Sinisa],
Hampali, S.[Shreyas],
Rad, M.[Mahdi],
Sarkar, S.D.[Sayan Deb],
Fraundorfer, F.[Friedrich],
Lepetit, V.[Vincent],
General 3d Room Layout from a Single View by Render-and-compare,
ECCV20(XVI: 187-203).
Springer DOI
2010
BibRef
Shi, X.P.[Xue-Peng],
Chen, Z.X.[Zhi-Xiang],
Kim, T.K.[Tae-Kyun],
Distance-normalized Unified Representation for Monocular 3d Object
Detection,
ECCV20(XXIX: 91-107).
Springer DOI
2010
BibRef
Zeng, W.[Wei],
Karaoglu, S.[Sezer],
Gevers, T.[Theo],
Joint 3d Layout and Depth Prediction from a Single Indoor Panorama
Image,
ECCV20(XVI: 666-682).
Springer DOI
2010
BibRef
Toft, C.[Carl],
Turmukhambetov, D.[Daniyar],
Sattler, T.[Torsten],
Kahl, F.[Fredrik],
Brostow, G.J.[Gabriel J.],
Single-image Depth Prediction Makes Feature Matching Easier,
ECCV20(XVI: 473-492).
Springer DOI
2010
BibRef
Wu, H.T.[Hong-Tao],
Meng, Y.[Ying],
Niu, B.Q.[Bing-Qing],
A Novel 3D Surface Reconstruction Method with Posterior Constraints
of Edge Detection,
ICIVC20(55-58)
IEEE DOI
2009
Image reconstruction, Calibration,
Feature extraction, Image edge detection, Digital cameras,
Feature point matching
BibRef
Peluso, V.,
Cipolletta, A.,
Calimera, A.,
Poggi, M.,
Tosi, F.,
Aleotti, F.,
Mattoccia, S.,
Enabling monocular depth perception at the very edge,
LPCV20(1581-1583)
IEEE DOI
2008
Estimation, Monitoring,
Microcontrollers, Computer architecture, Pattern recognition
BibRef
Ramamonjisoa, M.,
Du, Y.,
Lepetit, V.,
Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth
Estimation Using Displacement Fields,
CVPR20(14636-14645)
IEEE DOI
2008
Image reconstruction, Estimation, Machine learning,
Training, Task analysis, Manuals
BibRef
Spencer, J.,
Bowden, R.,
Hadfield, S.,
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised
Representation Learning,
CVPR20(14390-14401)
IEEE DOI
2008
Estimation, Robustness, Task analysis, Training, Feature extraction,
Decoding, Meteorology
BibRef
Johnston, A.,
Carneiro, G.,
Self-Supervised Monocular Trained Depth Estimation Using
Self-Attention and Discrete Disparity Volume,
CVPR20(4755-4764)
IEEE DOI
2008
Estimation, Uncertainty, Videos, Training, Computational modeling,
Convolution, Cameras
BibRef
Guizilini, V.,
Ambru?, R.,
Pillai, S.,
Raventos, A.,
Gaidon, A.,
3D Packing for Self-Supervised Monocular Depth Estimation,
CVPR20(2482-2491)
IEEE DOI
2008
Estimation, Training, Image resolution,
Cameras, Laser radar, Task analysis
BibRef
Henzler, P.,
Mitra, N.J.,
Ritschel, T.,
Learning a Neural 3D Texture Space From 2D Exemplars,
CVPR20(8353-8361)
IEEE DOI
2008
Stochastic processes, Interpolation, Decoding, Graphics, Training
BibRef
Xia, Z.,
Sullivan, P.,
Chakrabarti, A.,
Generating and Exploiting Probabilistic Monocular Depth Estimates,
CVPR20(62-71)
IEEE DOI
2008
Task analysis, Color, Estimation, Probabilistic logic, Training,
Probability distribution, Sensors
BibRef
Watson, J.[Jamie],
Firman, M.[Michael],
Monszpart, A.[Aron],
Brostow, G.J.[Gabriel J.],
Footprints and Free Space From a Single Color Image,
CVPR20(11-20)
IEEE DOI
2008
Geometry, Cameras, Image segmentation, Color, Task analysis,
Robot vision systems
BibRef
Yao, Y.,
Schertler, N.,
Rosales, E.,
Rhodin, H.,
Sigal, L.,
Sheffer, A.,
Front2Back: Single View 3D Shape Reconstruction via Front to Back
Prediction,
CVPR20(528-537)
IEEE DOI
2008
Surface reconstruction,
Image reconstruction, Shape, Geometry, Task analysis
BibRef
Wang, L.,
Zhang, J.,
Wang, O.,
Lin, Z.,
Lu, H.,
SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth
Estimation,
CVPR20(538-547)
IEEE DOI
2008
Semantics, Estimation, Image segmentation, Decoding,
Feature extraction, Predictive models, Task analysis
BibRef
Baradad, M.,
Torralba, A.,
Height and Uprightness Invariance for 3D Prediction From a Single
View,
CVPR20(488-497)
IEEE DOI
2008
Cameras, Training, Semantics,
Task analysis, Measurement, Solid modeling
BibRef
Chen, W.,
Qian, S.,
Fan, D.,
Kojima, N.,
Hamilton, M.,
Deng, J.,
OASIS: A Large-Scale Dataset for Single Image 3D in the Wild,
CVPR20(676-685)
IEEE DOI
2008
Surface reconstruction,
Image reconstruction, Task analysis, Shape, Geometry, Face
BibRef
Xian, K.,
Zhang, J.,
Wang, O.,
Mai, L.,
Lin, Z.,
Cao, Z.,
Structure-Guided Ranking Loss for Single Image Depth Prediction,
CVPR20(608-617)
IEEE DOI
2008
Image edge detection, Training,
Sensors, Task analysis, Videos, Measurement
BibRef
Yang, H.,
Carlone, L.,
In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction From 2D
Landmarks,
CVPR20(618-627)
IEEE DOI
2008
Shape, Image reconstruction,
Optimization, Solid modeling, Robustness
BibRef
Li, Z.Q.[Zheng-Qin],
Shi, J.[Jia],
Bi, S.[Sai],
Zhu, R.[Rui],
Sunkavalli, K.[Kalyan],
Haan, M.[Milo],
Xu, Z.X.[Ze-Xiang],
Ramamoorthi, R.[Ravi],
Chandraker, M.[Manmohan],
Physically-Based Editing of Indoor Scene Lighting from a Single Image,
ECCV22(VI:555-572).
Springer DOI
2211
BibRef
Li, Z.Q.[Zheng-Qin],
Shafiei, M.,
Ramamoorthi, R.,
Sunkavalli, K.[Kalyan],
Chandraker, M.[Manmohan],
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying
Lighting and SVBRDF From a Single Image,
CVPR20(2472-2481)
IEEE DOI
2008
Lighting, Rendering (computer graphics), Geometry, Training, Shape,
Image reconstruction, Task analysis
BibRef
Li, Y.,
Mao, J.,
Zhang, X.,
Freeman, W.T.,
Tenenbaum, J.B.,
Wu, J.,
Perspective Plane Program Induction From a Single Image,
CVPR20(4433-4442)
IEEE DOI
2008
Cameras, Graphics, Task analysis,
Lattices, Inference algorithms
BibRef
Chen, Q.,
Nguyen, V.,
Han, F.,
Kiveris, R.,
Tu, Z.,
Topology-Aware Single-Image 3D Shape Reconstruction,
L3DGM20(1089-1097)
IEEE DOI
2008
Shape, Image reconstruction, Decoding,
Topology, Training
BibRef
Pokale, A.,
Aggarwal, A.,
Jatavallabhula, K.M.,
Krishna, K.M.[K. Madhava],
Reconstruct, Rasterize and Backprop: Dense shape and pose estimation
from a single image,
VisualSLAM20(179-186)
IEEE DOI
2008
Shape, Image reconstruction, Cameras,
Task analysis, Simultaneous localization and mapping, Neural networks
BibRef
Onizuka, H.,
Hayirci, Z.,
Thomas, D.,
Sugimoto, A.,
Uchiyama, H.,
Taniguchi, R.,
TetraTSDF: 3D Human Reconstruction From a Single Image With a
Tetrahedral Outer Shell,
CVPR20(6010-6019)
IEEE DOI
2008
Shape, Solid modeling,
Image reconstruction, Biological system modeling,
Task analysis
BibRef
Schurischuster, S.[Stefan],
Loaiciga R, J.M.[Jorge Mario],
Kurtic, A.[Andrija],
Sablatnig, R.[Robert],
In-Time 3D Reconstruction and Instance Segmentation from Monocular
Sensor Data,
CRV20(142-149)
IEEE DOI
2006
BibRef
Mani, K.,
Daga, S.,
Garg, S.,
Shankar, N.S.,
Murthy, J.K.[J. Krishna],
Krishna, K.M.,
Mono Lay out: Amodal scene layout from a single image,
WACV20(1678-1686)
IEEE DOI
2006
Layout, Roads, Vehicle dynamics, Estimation, Decoding,
Feature extraction, Task analysis
BibRef
Nguyen, D.[Duc],
Choi, S.[Seonghwa],
Kim, W.[Woojae],
Lee, S.H.[Sang-Hoon],
GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion,
ICCV19(8627-8636)
IEEE DOI
2004
Reconstruct point cloud from single image.
feature extraction, graph theory, image reconstruction,
solid modelling, feature blending,
Computational modeling
BibRef
Ye, Y.F.[Yu-Fei],
Tulsiani, S.[Shubham],
Gupta, A.[Abhinav],
Shelf-Supervised Mesh Prediction in the Wild,
CVPR21(8839-8848)
IEEE DOI
2111
Visualization, Shape, Scalability,
Lighting, Predictive models, Rendering (computer graphics)
BibRef
Kulkarni, N.[Nilesh],
Misra, I.[Ishan],
Tulsiani, S.[Shubham],
Gupta, A.[Abhinav],
3D-RelNet: Joint Object and Relational Network for 3D Prediction,
ICCV19(2212-2221)
IEEE DOI
2004
learning (artificial intelligence), pose estimation,
solid modelling, relational network, independent predictions,
BibRef
Zhao, Y.,
Kong, S.,
Shin, D.,
Fowlkes, C.C.,
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real
Domain Shift and Improve Depth Estimation,
CVPR20(3327-3337)
IEEE DOI
2008
Training, Task analysis, Training data, Predictive models,
Adaptation models, Data models, Clutter
BibRef
Cha, G.,
Lee, M.,
Oh, S.,
Unsupervised 3D Reconstruction Networks,
ICCV19(3848-3857)
IEEE DOI
2004
cameras, feature extraction, image motion analysis,
image reconstruction, pose estimation, shape recognition,
Structure from motion
BibRef
Huang, J.,
Zhou, Y.,
Funkhouser, T.,
Guibas, L.J.,
FrameNet: Learning Local Canonical Frames of 3D Surfaces From a
Single RGB Image,
ICCV19(8637-8646)
IEEE DOI
2004
augmented reality, computational geometry, computer graphics,
feature extraction, geometry, image colour analysis, Robustness
BibRef
Gadelha, M.[Matheus],
RoyChowdhury, A.[Aruni],
Sharma, G.[Gopal],
Kalogerakis, E.[Evangelos],
Cao, L.L.[Liang-Liang],
Learned-Miller, E.G.[Erik G.],
Wang, R.[Rui],
Maji, S.[Subhransu],
Label-efficient Learning on Point Clouds Using Approximate Convex
Decompositions,
ECCV20(X:473-491).
Springer DOI
2011
BibRef
Ramamonjisoa, M.,
Lepetit, V.,
SharpNet: Fast and Accurate Recovery of Occluding Contours in
Monocular Depth Estimation,
3D-Wild19(2109-2118)
IEEE DOI
2004
augmented reality, cameras, image colour analysis,
image reconstruction, object recognition,
Surface Normal Estimation
BibRef
Watson, J.,
Firman, M.,
Brostow, G.,
Turmukhambetov, D.,
Self-Supervised Monocular Depth Hints,
ICCV19(2162-2171)
IEEE DOI
2004
regression analysis, stereo image processing,
supervised learning, monocular depth estimators, Laser radar
BibRef
Issaranon, T.,
Zou, C.,
Forsyth, D.,
Counterfactual Depth from a Single RGB Image,
3D-Wild19(2129-2138)
IEEE DOI
2004
decoding, geometry, image coding, image colour analysis,
image reconstruction, image representation, image resolution,
Object Removal
BibRef
Wallace, B.,
Hariharan, B.,
Few-Shot Generalization for Single-Image 3D Reconstruction via Priors,
ICCV19(3817-3826)
IEEE DOI
2004
image classification, image reconstruction,
stereo image processing, few-shot generalization,
Generators
BibRef
Godard, C.,
Aodha, O.M.,
Firman, M.,
Brostow, G.,
Digging Into Self-Supervised Monocular Depth Estimation,
ICCV19(3827-3837)
IEEE DOI
2004
distance measurement, image classification,
image motion analysis, image reconstruction, image sampling,
Image matching
BibRef
Zhang, Y.[Yinda],
Wadhwa, N.[Neal],
Orts-Escolano, S.[Sergio],
Häne, C.[Christian],
Fanello, S.[Sean],
Garg, R.[Rahul],
Du2net: Learning Depth Estimation from Dual-cameras and Dual-pixels,
ECCV20(I:582-598).
Springer DOI
2011
BibRef
Garg, R.[Rahul],
Wadhwa, N.[Neal],
Ansari, S.,
Barron, J.,
Learning Single Camera Depth Estimation Using Dual-Pixels,
ICCV19(7627-7636)
IEEE DOI
2004
cameras, image colour analysis, image matching, image sensors,
stereo image processing, supervised learning,
Training
BibRef
Pinheiro, P.O.,
Rostamzadeh, N.,
Ahn, S.,
Domain-Adaptive Single-View 3D Reconstruction,
ICCV19(7637-7646)
IEEE DOI
2004
image reconstruction, image representation,
learning (artificial intelligence),
Decoding
BibRef
Ho, C.H.[Chih-Hui],
Morgado, P.[Pedro],
Persekian, A.[Amir],
Vasconcelos, N.M.[Nuno M.],
PIEs: Pose Invariant Embeddings,
CVPR19(12369-12378).
IEEE DOI
2002
BibRef
Meng, Y.[Yue],
Lu, Y.X.[Yong-Xi],
Raj, A.[Aman],
Sunarjo, S.[Samuel],
Guo, R.[Rui],
Javidi, T.[Tara],
Bansal, G.[Gaurav],
Bharadia, D.[Dinesh],
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception,
CVPR19(9802-9812).
IEEE DOI
2002
BibRef
Manhardt, F.[Fabian],
Kehl, W.[Wadim],
Gaidon, A.[Adrien],
ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape,
CVPR19(2064-2073).
IEEE DOI
2002
BibRef
Weng, C.Y.[Chung-Yi],
Curless, B.[Brian],
Kemelmacher-Shlizerman, I.[Ira],
Photo Wake-Up: 3D Character Animation From a Single Photo,
CVPR19(5901-5910).
IEEE DOI
2002
BibRef
Riegler, G.[Gernot],
Liao, Y.[Yiyi],
Donne, S.[Simon],
Koltun, V.[Vladlen],
Geiger, A.[Andreas],
Connecting the Dots: Learning Representations for Active Monocular
Depth Estimation,
CVPR19(7616-7625).
IEEE DOI
2002
BibRef
Yang, Y.C.[Yan-Chao],
Wong, A.[Alex],
Soatto, S.[Stefano],
Dense Depth Posterior (DDP) From Single Image and Sparse Range,
CVPR19(3348-3357).
IEEE DOI
2002
BibRef
Wong, A.[Alex],
Soatto, S.[Stefano],
Bilateral Cyclic Constraint and Adaptive Regularization for
Unsupervised Monocular Depth Prediction,
CVPR19(5637-5646).
IEEE DOI
2002
BibRef
Lee, J.H.[Jae-Han],
Kim, C.S.[Chang-Su],
Monocular Depth Estimation Using Relative Depth Maps,
CVPR19(9721-9730).
IEEE DOI
2002
BibRef
Pilzer, A.[Andrea],
Lathuiliere, S.[Stephane],
Sebe, N.[Nicu],
Ricci, E.[Elisa],
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge
Distillation for Unsupervised Monocular Depth Estimation,
CVPR19(9760-9769).
IEEE DOI
2002
BibRef
Zhao, S.S.[Shan-Shan],
Fu, H.[Huan],
Gong, M.M.[Ming-Ming],
Tao, D.C.[Da-Cheng],
Geometry-Aware Symmetric Domain Adaptation for Monocular Depth
Estimation,
CVPR19(9780-9790).
IEEE DOI
2002
BibRef
Tosi, F.[Fabio],
Aleotti, F.[Filippo],
Poggi, M.[Matteo],
Mattoccia, S.[Stefano],
Learning Monocular Depth Estimation Infusing Traditional Stereo
Knowledge,
CVPR19(9791-9801).
IEEE DOI
2002
BibRef
Zhi, S.[Shuaifeng],
Bloesch, M.[Michael],
Leutenegger, S.[Stefan],
Davison, A.J.[Andrew J.],
SceneCode: Monocular Dense Semantic Reconstruction Using Learned
Encoded Scene Representations,
CVPR19(11768-11777).
IEEE DOI
2002
BibRef
Chen, P.Y.[Po-Yi],
Liu, A.H.[Alexander H.],
Liu, Y.C.[Yen-Cheng],
Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Towards Scene Understanding: Unsupervised Monocular Depth Estimation
With Semantic-Aware Representation,
CVPR19(2619-2627).
IEEE DOI
2002
BibRef
Tatarchenko, M.[Maxim],
Richter, S.R.[Stephan R.],
Ranftl, R.[Rene],
Li, Z.[Zhuwen],
Koltun, V.[Vladlen],
Brox, T.[Thomas],
What Do Single-View 3D Reconstruction Networks Learn?,
CVPR19(3400-3409).
IEEE DOI
2002
BibRef
Yu, Y.[Ye],
Smith, W.A.P.[William A. P.],
InverseRenderNet: Learning Single Image Inverse Rendering,
CVPR19(3150-3159).
IEEE DOI
2002
BibRef
Kato, H.[Hiroharu],
Harada, T.[Tatsuya],
Learning View Priors for Single-View 3D Reconstruction,
CVPR19(9770-9779).
IEEE DOI
2002
BibRef
Wei, Y.[Yi],
Liu, S.H.[Shao-Hui],
Zhao, W.[Wang],
Lu, J.W.[Ji-Wen],
Conditional Single-View Shape Generation for Multi-View Stereo
Reconstruction,
CVPR19(9643-9652).
IEEE DOI
2002
BibRef
Gur, S.[Shir],
Wolf, L.B.[Lior B.],
Single Image Depth Estimation Trained via Depth From Defocus Cues,
CVPR19(7675-7684).
IEEE DOI
2002
BibRef
Jack, D.[Dominic],
Maire, F.[Frederic],
Shirazi, S.[Sareh],
Eriksson, A.[Anders],
IGE-Net: Inverse Graphics Energy Networks for Human Pose Estimation and
Single-View Reconstruction,
CVPR19(7068-7077).
IEEE DOI
2002
BibRef
Chen, W.F.[Wei-Feng],
Qian, S.Y.[Sheng-Yi],
Deng, J.[Jia],
Learning Single-Image Depth From Videos Using Quality Assessment
Networks,
CVPR19(5597-5606).
IEEE DOI
2002
BibRef
Facil, J.M.[Jose M.],
Ummenhofer, B.[Benjamin],
Zhou, H.Z.[Hui-Zhong],
Montesano, L.[Luis],
Brox, T.[Thomas],
Civera, J.[Javier],
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth,
CVPR19(11818-11827).
IEEE DOI
2002
BibRef
Kaushik, V.,
Lall, B.,
UnDispNet: Unsupervised Learning for Multi-Stage Monocular Depth
Prediction,
3DV19(633-642)
IEEE DOI
1911
Training, Estimation, Image resolution, Image reconstruction,
Computer architecture, Cameras, Depth Prediction
BibRef
Grabner, A.,
Roth, P.M.,
Lepetit, V.,
Location Field Descriptors:
Single Image 3D Model Retrieval in the Wild,
3DV19(583-593)
IEEE DOI
1806
Solid modeling,
Computational modeling, Shape, Task analysis, Feature extraction, 3D Pose
BibRef
Elkerdawy, S.,
Zhang, H.,
Ray, N.,
Lightweight Monocular Depth Estimation Model by Joint End-to-End
Filter Pruning,
ICIP19(4290-4294)
IEEE DOI
1910
Monocular depth estimation, Filter pruning, Model compression
BibRef
Atapour-Abarghouei, A.[Amir],
Breckon, T.P.[Toby P.],
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled
by a Multi-Task Geometric and Semantic Scene Understanding Approach,
CVPR19(3368-3379).
IEEE DOI
2002
BibRef
Lu, G.Y.[Guo-Yu],
Han, Y.H.[Ya-Hong],
3D Shape Retrieval through Multilayer RBF Neural Network,
ICIP19(2394-2398)
IEEE DOI
1910
3D Object Retrieval, RBF Neural Network, Multilayer Perceptron
BibRef
Zou, H.,
Xian, K.,
Yang, J.,
Cao, Z.,
Mean-Variance Loss for Monocular Depth Estimation,
ICIP19(1760-1764)
IEEE DOI
1910
mean-variance loss, monocular depth estimation, classification
BibRef
Xiong, X.,
Cao, Z.,
Zhang, C.,
Xian, K.,
Zou, H.,
Binoboost: Boosting Self-Supervised Monocular Depth Prediction with
Binocular Guidance,
ICIP19(1770-1774)
IEEE DOI
1910
Self-supervised, Monocular depth prediction, Binocular guidance
BibRef
Jiang, H.,
Huang, R.,
High Quality Monocular Depth Estimation Via A Multi-Scale Network And
A Detail-Preserving Objective,
ICIP19(1920-1924)
IEEE DOI
1910
Monocular Depth Estimation, MultiScale Network, Detail-Preserving Loss
BibRef
Batavia, D.[Darshan],
Hladuvka, J.[Jirí],
Kropatsch, W.G.[Walter G.],
Partitioning 2D Images into Prototypes of Slope Region,
CAIP19(I:363-374).
Springer DOI
1909
BibRef
Jack, D.[Dominic],
Maire, F.[Frederic],
Denman, S.[Simon],
Eriksson, A.[Anders],
Sparse Convolutions on Continuous Domains for Point Cloud and Event
Stream Networks,
ACCV20(I:400-416).
Springer DOI
2103
BibRef
Michalkiewicz, M.,
Pontes, J.K.,
Jack, D.,
Baktashmotlagh, M.,
Eriksson, A.,
Implicit Surface Representations As Layers in Neural Networks,
ICCV19(4742-4751)
IEEE DOI
2004
image reconstruction, image representation,
neural net architecture, implicit surface representations, Geometry
BibRef
Jack, D.[Dominic],
Pontes, J.K.[Jhony K.],
Sridharan, S.[Sridha],
Fookes, C.[Clinton],
Shirazi, S.[Sareh],
Maire, F.[Frederic],
Eriksson, A.[Anders],
Learning Free-Form Deformations for 3D Object Reconstruction,
ACCV18(II:317-333).
Springer DOI
1906
BibRef
Pontes, J.K.[Jhony K.],
Kong, C.[Chen],
Sridharan, S.[Sridha],
Lucey, S.[Simon],
Eriksson, A.[Anders],
Fookes, C.[Clinton],
Image2Mesh: A Learning Framework for Single Image 3D Reconstruction,
ACCV18(I:365-381).
Springer DOI
1906
BibRef
Ochs, M.[Matthias],
Kretz, A.[Adrian],
Mester, R.[Rudolf],
SDNet: Semantically Guided Depth Estimation Network,
GCPR19(288-302).
Springer DOI
1911
BibRef
Brickwedde, F.[Fabian],
Abraham, S.[Steffen],
Mester, R.[Rudolf],
Exploiting Single Image Depth Prediction for Mono-stixel Estimation,
CVRoads18(I:240-255).
Springer DOI
1905
BibRef
Stathopoulou, E.K.,
Remondino, F.,
Semantic Photogrammetry: Boosting Image-based 3D Reconstruction With
Semantic Labeling,
3DARCH19(685-690).
DOI Link
1904
BibRef
Yusiong, J.P.,
Naval, P.,
AsiANet: Autoencoders in Autoencoder for Unsupervised Monocular Depth
Estimation,
WACV19(443-451)
IEEE DOI
1904
image classification, image motion analysis,
learning (artificial intelligence), neural nets,
Network architecture
BibRef
Kumar, A.C.S.[Arun C.S.],
Bhandarkar, S.M.[Suchendra M.],
Prasad, M.[Mukta],
Learning Hierarchical Models for Class-Specific Reconstruction from
Natural Data,
AutoDrive18(1170-11708)
IEEE DOI
1812
Shape, Solid modeling, Image reconstruction, Deformable models,
Strain
BibRef
Tulsiani, S.[Shubham],
Efros, A.A.[Alexei A.],
Malik, J.[Jitendra],
Multi-view Consistency as Supervisory Signal for Learning Shape and
Pose Prediction,
CVPR18(2897-2905)
IEEE DOI
1812
Shape, Training, Geometry, Cameras,
Loss measurement, Image reconstruction
BibRef
Tulsiani, S.[Shubham],
Gupta, S.[Saurabh],
Fouhey, D.[David],
Efros, A.A.[Alexei A.],
Malik, J.[Jitendra],
Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene,
CVPR18(302-310)
IEEE DOI
1812
Shape, Layout, Proposals, Image resolution, Standards
BibRef
Srinivasan, P.P.,
Garg, R.,
Wadhwa, N.,
Ng, R.,
Barron, J.T.,
Aperture Supervision for Monocular Depth Estimation,
CVPR18(6393-6401)
IEEE DOI
1812
Apertures, Cameras, Rendering (computer graphics), Estimation,
Geometry, Prediction algorithms, Three-dimensional displays
BibRef
Xian, K.,
Shen, C.,
Cao, Z.,
Lu, H.,
Xiao, Y.,
Li, R.,
Luo, Z.,
Monocular Relative Depth Perception with Web Stereo Data Supervision,
CVPR18(311-320)
IEEE DOI
1812
Training, Measurement, Task analysis, Semantics, Estimation,
Image segmentation, Network architecture
BibRef
Niu, C.,
Li, J.,
Xu, K.,
Im2Struct: Recovering 3D Shape Structure from a Single RGB Image,
CVPR18(4521-4529)
IEEE DOI
1812
Shape, Solid modeling, Periodic structures, Image reconstruction
BibRef
Zou, C.,
Colburn, A.,
Shan, Q.,
Hoiem, D.,
LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image,
CVPR18(2051-2059)
IEEE DOI
1812
Layout, Convolution, Training, Cameras, Estimation
BibRef
Ranade, S.[Siddhant],
Yu, X.[Xin],
Kakkar, S.[Shantnu],
Miraldo, P.[Pedro],
Ramalingam, S.[Srikumar],
Mapping of Sparse 3d Data Using Alternating Projection,
ACCV20(I:295-313).
Springer DOI
2103
BibRef
Kim, S.,
Manduchi, R.,
Qin, S.,
Multi-planar Monocular Reconstruction of Manhattan Indoor Scenes,
3DV18(616-624)
IEEE DOI
1812
cameras, computational geometry, image matching,
image motion analysis, image reconstruction, image sequences,
Plane Reconstruction
BibRef
Pan, J.,
Li, J.,
Han, X.,
Jia, K.,
Residual MeshNet:
Learning to Deform Meshes for Single-View 3D Reconstruction,
3DV18(719-727)
IEEE DOI
1812
approximation theory, image reconstruction,
learning (artificial intelligence), mesh generation, neural nets,
Mesh
BibRef
Hao, Z.X.[Zhi-Xiang],
Li, Y.[Yu],
You, S.D.[Shao-Di],
Lu, F.[Feng],
Detail Preserving Depth Estimation from a Single Image Using
Attention Guided Networks,
3DV18(304-313)
IEEE DOI
1812
convolution, feature extraction, feedforward neural nets,
image classification, image resolution,
attention mechanism
BibRef
Poggi, M.,
Tosi, F.,
Mattoccia, S.,
Learning Monocular Depth Estimation with Unsupervised Trinocular
Assumptions,
3DV18(324-333)
IEEE DOI
1812
image motion analysis, image reconstruction, image sensors,
learning (artificial intelligence), stereo image processing,
trinocular
BibRef
Bednarik, J.,
Fua, P.,
Salzmann, M.,
Learning to Reconstruct Texture-Less Deformable Surfaces from a
Single View,
3DV18(606-615)
IEEE DOI
1812
image reconstruction, image representation,
learning (artificial intelligence), mesh generation,
shape recovery
BibRef
Lee, J.,
Heo, M.,
Kim, K.,
Kim, C.,
Single-Image Depth Estimation Based on Fourier Domain Analysis,
CVPR18(330-339)
IEEE DOI
1812
Estimation, Feature extraction, Frequency-domain analysis,
Reliability, Discrete Fourier transforms,
Image reconstruction
BibRef
Li, Z.,
Snavely, N.,
MegaDepth: Learning Single-View Depth Prediction from Internet Photos,
CVPR18(2041-2050)
IEEE DOI
1812
Semantics, Image reconstruction,
Training data, Internet, Training, Image segmentation
BibRef
Sun, X.,
Wu, J.,
Zhang, X.,
Zhang, Z.,
Zhang, C.,
Xue, T.,
Tenenbaum, J.B.,
Freeman, W.T.,
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling,
CVPR18(2974-2983)
IEEE DOI
1812
Shape, Solid modeling,
Benchmark testing, Pose estimation, Image reconstruction
BibRef
Shin, D.,
Fowlkes, C.C.,
Hoiem, D.,
Pixels, Voxels, and Views: A Study of Shape Representations for
Single View 3D Object Shape Prediction,
CVPR18(3061-3069)
IEEE DOI
1812
Shape, Solid modeling,
Predictive models, Decoding, Training, Automobiles
BibRef
Pumarola, A.,
Agudo, A.,
Porzi, L.,
Sanfeliu, A.,
Lepetit, V.,
Moreno-Noguer, F.,
Geometry-Aware Network for Non-rigid Shape Prediction from a Single
View,
CVPR18(4681-4690)
IEEE DOI
1812
Shape,
Surface reconstruction, Strain, Image reconstruction, Surface texture
BibRef
Chen, Z.[Zhao],
Badrinarayanan, V.[Vijay],
Drozdov, G.[Gilad],
Rabinovich, A.[Andrew],
Estimating Depth from RGB and Sparse Sensing,
ECCV18(II: 176-192).
Springer DOI
1810
BibRef
Clark, R.[Ronald],
Bloesch, M.[Michael],
Czarnowski, J.[Jan],
Leutenegger, S.[Stefan],
Davison, A.J.[Andrew J.],
Learning to Solve Nonlinear Least Squares for Monocular Stereo,
ECCV18(VIII: 291-306).
Springer DOI
1810
BibRef
Heo, M.[Minhyeok],
Lee, J.[Jaehan],
Kim, K.R.[Kyung-Rae],
Kim, H.U.[Han-Ul],
Kim, C.S.[Chang-Su],
Monocular Depth Estimation Using Whole Strip Masking and
Reliability-Based Refinement,
ECCV18(II: 39-55).
Springer DOI
1810
BibRef
Zhong, Y.R.[Yi-Ran],
Dai, Y.C.[Yu-Chao],
Li, H.D.[Hong-Dong],
Stereo Computation for a Single Mixture Image,
ECCV18(IX: 441-456).
Springer DOI
1810
BibRef
Huang, S.Y.[Si-Yuan],
Qi, S.Y.[Si-Yuan],
Zhu, Y.X.[Yi-Xin],
Xiao, Y.[Yinxue],
Xu, Y.[Yuanlu],
Zhu, S.C.[Song-Chun],
Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image,
ECCV18(VII: 194-211).
Springer DOI
1810
BibRef
Jiao, J.B.[Jian-Bo],
Cao, Y.[Ying],
Song, Y.B.[Yi-Bing],
Lau, R.[Rynson],
Look Deeper into Depth: Monocular Depth Estimation with Semantic
Booster and Attention-Driven Loss,
ECCV18(XV: 55-71).
Springer DOI
1810
BibRef
Guo, X.Y.[Xiao-Yang],
Li, H.S.[Hong-Sheng],
Yi, S.[Shuai],
Ren, J.[Jimmy],
Wang, X.G.[Xiao-Gang],
Learning Monocular Depth by Distilling Cross-Domain Stereo Networks,
ECCV18(XI: 506-523).
Springer DOI
1810
BibRef
Wang, N.Y.[Nan-Yang],
Zhang, Y.[Yinda],
Li, Z.W.[Zhu-Wen],
Fu, Y.W.[Yan-Wei],
Liu, W.[Wei],
Jiang, Y.G.[Yu-Gang],
Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images,
ECCV18(XI: 55-71).
Springer DOI
1810
BibRef
Gan, Y.K.[Yu-Kang],
Xu, X.Y.[Xiang-Yu],
Sun, W.X.[Wen-Xiu],
Lin, L.[Liang],
Monocular Depth Estimation with Affinity, Vertical Pooling, and Label
Enhancement,
ECCV18(III: 232-247).
Springer DOI
1810
BibRef
Zheng, C.X.[Chuan-Xia],
Cham, T.J.[Tat-Jen],
Cai, J.F.[Jian-Fei],
T2Net: Synthetic-to-Realistic Translation for Solving Single-Image
Depth Estimation Tasks,
ECCV18(VII: 798-814).
Springer DOI
1810
BibRef
Yang, G.[Guandao],
Cui, Y.[Yin],
Belongie, S.[Serge],
Hariharan, B.[Bharath],
Learning Single-View 3D Reconstruction with Limited Pose Supervision,
ECCV18(XV: 90-105).
Springer DOI
1810
BibRef
Wu, J.J.[Jia-Jun],
Zhang, C.K.[Cheng-Kai],
Zhang, X.M.[Xiu-Ming],
Zhang, Z.T.[Zhou-Tong],
Freeman, W.T.[William T.],
Tenenbaum, J.B.[Joshua B.],
Learning Shape Priors for Single-View 3D Completion And Reconstruction,
ECCV18(XI: 673-691).
Springer DOI
1810
BibRef
Jayaraman, D.[Dinesh],
Gao, R.[Ruohan],
Grauman, K.[Kristen],
ShapeCodes: Self-supervised Feature Learning by Lifting Views to
Viewgrids,
ECCV18(XVI: 126-144).
Springer DOI
1810
BibRef
Tian, H.,
Li, F.,
Depth Prediction From a Single Image with 3D Consistency,
ICIP18(111-115)
IEEE DOI
1809
Image color analysis, Training,
Distortion, Color, Computer architecture, Solid modeling,
random projection
BibRef
Kurenkov, A.,
Ji, J.,
Garg, A.,
Mehta, V.,
Gwak, J.,
Choy, C.,
Savarese, S.,
DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction
from a Single Image,
WACV18(858-866)
IEEE DOI
1806
CAD, augmented reality, image reconstruction,
learning (artificial intelligence), object recognition,
BibRef
Nimisha, T.M.,
Mathamkode, A.[Arun],
Ambasamudram, R.[Rajagopalan],
Dictionary Replacement for Single Image Restoration of 3D Scenes,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Schubert, D.[David],
Demmel, N.[Nikolaus],
Usenko, V.[Vladyslav],
Stückler, J.[Jörg],
Cremers, D.[Daniel],
Direct Sparse Odometry with Rolling Shutter,
ECCV18(VIII: 699-714).
Springer DOI
1810
BibRef
Yao, Q.,
Luo, G.,
Zhu, Y.,
Depth estimation for outdoor image using couple dictionary learning
and region detection,
VCIP17(1-4)
IEEE DOI
1804
edge detection, image representation,
image retrieval, learning (artificial intelligence),
single image depth estimation
BibRef
Guo, X.,
Nguyen, K.,
Denman, S.,
Fookes, C.,
Sridharan, S.,
Single image depth prediction using super-column super-pixel features,
ICIP17(2657-2661)
IEEE DOI
1803
Error analysis, Feature extraction, Image color analysis,
Image segmentation, Interpolation, Task analysis, Training, depth,
super pixel
BibRef
Chen, Y.,
Wang, F.,
Wang, X.,
Recovering complex non-rigid 3D structures from monocular images by
union of nonlinear subspaces,
ICIP17(2622-2626)
IEEE DOI
1803
Cameras, Kernel, Radio frequency, Shape,
Trajectory,
subspace clustering
BibRef
Baig, M.H.[Mohammad Haris],
Torresani, L.[Lorenzo],
Coupled depth learning,
WACV16(1-10)
IEEE DOI
1606
Computational modeling.
Depth from single image via learning.
BibRef
Akhmadeev, F.[Foat],
Surface Prediction for a Single Image of Urban Scenes,
AutoSystems14(369-382).
Springer DOI
1504
BibRef
Ikeoka, H.[Hiroshi],
Murata, T.[Takafumi],
Okuwaki, M.[Maiki],
Hamamoto, T.[Takayuki],
Depth estimation for automotive with tilted optics imaging,
ICIP14(3852-3856)
IEEE DOI
1502
Automotive engineering
BibRef
Li, H.S.[Hong-Song],
Song, T.[Ting],
Wu, Z.H.[Ze-Huan],
Ma, J.D.[Jian-Dong],
Ding, G.Y.[Gang-Yi],
Reconstruction of a Complex Mirror Surface from a Single Image,
ISVC14(I: 402-412).
Springer DOI
1501
Use the multiple reflections of same environment point.
BibRef
Liu, M.M.[Miao-Miao],
Salzmann, M.[Mathieu],
He, X.M.[Xu-Ming],
Discrete-Continuous Depth Estimation from a Single Image,
CVPR14(716-723)
IEEE DOI
1409
BibRef
Cheng, H.M.[Hsin-Min],
Tseng, C.Y.[Chen-Yu],
Hsin, C.H.[Cheng-Ho],
Wang, S.J.[Sheng-Jyh],
Single-image 3-D depth estimation for urban scenes,
ICIP13(2121-2125)
IEEE DOI
1402
3-D depth recovery;Depth estimation
BibRef
Chapter on 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings continues in
Single View 3D Reconstruction, Convolutional Neural Networks, CNN .