9.8.1 Single Image, Single View 3D Reconstruction, Learning

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

Santos, R.[Roi], Pardo, X.M.[Xose M.], Fdez-Vidal, X.R.[Xose R.],
Scene wireframes sketching for Unmanned Aerial Vehicles,
PR(86), 2019, pp. 354-367.
Elsevier DOI 1811
3D abstraction, Reconstruction, Line-based sketching, UAV 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

Xia, Y.[Yan], Wang, C.[Cheng], Xu, Y.S.[Yu-Sheng], Zang, Y.[Yu], Liu, W.[Weiquan], Li, J.[Jonathan], Stilla, U.[Uwe],
RealPoint3D: Generating 3D Point Clouds from a Single Image of Complex Scenarios,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
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

Luo, N.[Nan], Huang, L.[Ling], Wang, Q.[Quan], Liu, G.[Gang],
An Improved Algorithm Robust to Illumination Variations for Reconstructing Point Cloud Models from Images,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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

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

Yang, J.L.[Jing-Lun], Li, Y.[Youhua], Yang, L.[Lu],
Shape transformer nets: Generating viewpoint-invariant 3D shapes from a single image,
JVCIR(81), 2021, pp. 103345.
Elsevier DOI 2112
3D shape generation, Invariant viewpoint, Disentanglement, B-spline surfaces 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

Tian, F.Z.[Fang-Zheng], Gao, Y.B.[Yong-Bin], Fang, Z.J.[Zhi-Jun], Fang, Y.M.[Yu-Ming], Gu, J.[Jia], Fujita, H.[Hamido], Hwang, J.N.[Jenq-Neng],
Depth Estimation Using a Self-Supervised Network Based on Cross-Layer Feature Fusion and the Quadtree Constraint,
CirSysVideo(32), No. 4, April 2022, pp. 1751-1766.
IEEE DOI 2204
Use relative pose to synthesize the target image from the reference image. Estimation, Cameras, Semantics, Training, Deep learning, Geometry, Depth map estimation, self-supervised learning, feature fusion 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.[Fengyi], 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

Xu, Y.L.[Yuan-Lu], Wang, W.G.[Wen-Guan], Liu, T.Y.[Teng-Yu], Liu, X.B.[Xiao-Bai], Xie, J.W.[Jian-Wen], Zhu, S.C.[Song-Chun],
Monocular 3D Pose Estimation via Pose Grammar and Data Augmentation,
PAMI(44), No. 10, October 2022, pp. 6327-6344.
IEEE DOI 2209
Grammar, Pose estimation, Cameras, Solid modeling, Training, Protocols, 3D pose estimation, dependency grammar, data augmentation, learning-by-synthesis BibRef

Xie, J.W.[Jian-Wen], Zheng, Z.L.[Zi-Long], Gao, R.Q.[Rui-Qi], Wang, W.G.[Wen-Guan], Zhu, S.C.[Song-Chun], Wu, Y.N.[Ying Nian],
Learning Descriptor Networks for 3D Shape Synthesis and Analysis,
CVPR18(8629-8638)
IEEE DOI 1812
Solid modeling, Shape, Data models, Training, Generators, Analytical models 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

Xing, X.X.[Xiao-Xia], Cai, Y.[Yinghao], Lu, T.[Tao], Yang, Y.P.[Yi-Ping], Wen, D.[Dayong],
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

Patiño, 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],
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.[Yijiang], 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.[Yuyan], 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

Qin, Z.[Zequn], Li, X.[Xi],
MonoGround: Detecting Monocular 3D Objects from the Ground,
CVPR22(3783-3792)
IEEE DOI 2210
Training, Laser radar, Costs, Soft sensors, Estimation, 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

Xu, Y.[Yinghao], Peng, S.[Sida], Yang, C.[Ceyuan], Shen, Y.J.[Yu-Jun], Zhou, B.[Bolei],
3D-aware Image Synthesis via Learning Structural and Textural Representations,
CVPR22(18409-18418)
IEEE DOI 2210
Solid modeling, Image synthesis, Shape, Generative adversarial networks, Rendering (computer graphics), 3D from single images BibRef

Zohaib, M.[Mohammad], Taiana, M.[Matteo], del Bue, A.[Alessio],
Towards Reconstruction of 3D Shapes in a Realistic Environment,
CIAP22(II:3-14).
Springer DOI 2205
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.[Zhenbo], 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

Ji, P.[Pan], Li, R.[Runze], Bhanu, B.[Bir], Xu, Y.[Yi],
MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments,
ICCV21(12767-12776)
IEEE DOI 2203
Pose estimation, Predictive models, Cameras, Indoor environment, 3D from a single image and shape-from-x, Transfer/Low-shot/Semi/Unsupervised Learning 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], Åström, 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.[Yuyan], 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

Li, Z.[Zuoyue], Fan, T.X.[Tian-Xing], Li, Z.Q.[Zhen-Qiang], Cui, Z.P.[Zhao-Peng], Sato, Y.[Yoichi], Pollefeys, M.[Marc], Oswald, M.R.[Martin R.],
CompNVS: Novel View Synthesis with Scene Completion,
ECCV22(I:447-463).
Springer DOI 2211
BibRef

Bauer, Z.[Zuria], Li, Z.[Zuoyue], Orts-Escolano, S.[Sergio], Cazorla, M.[Miguel], Pollefeys, M.[Marc], Oswald, M.R.[Martin R.],
NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis,
3DV21(848-858)
IEEE DOI 2201
Training, Measurement, Art, Image synthesis, Pipelines, Buildings, monocular depth, novel view synthesis, depth prediction 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

Takeyama, K.[Kojiro],
3D Reconstruction of Edge Line by ICP-based Matching with Geometric Constraints,
DICTA20(1-8)
IEEE DOI 2201
Iterative closest point algorithm, Image edge detection, Estimation, Cameras, Robustness, Strain, SFM, spatial map, edge line, iterative closest point algorithm BibRef

Li, K.[Keyao], Li, G.[Ge], Li, T.[Thomas],
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

Souza, M.R.[Marcos R.], Conceição, J.S.[Jhonatas S.], Flores-Campana, J.L.[Jose L.], Decker, L.G.L.[Luis G. L.], Luvizon, D.C.[Diogo C.], Carvalho, G.S.P.[Gustavo Sutter P.], Maia, H.A.[Helena A.], Pedrini, H.[Helio],
Pyramidal Layered Scene Inference with Image Outpainting for Monocular View Synthesis,
CAIP21(I:37-46).
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

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

Liu, F.[Feng], Tran, L.[Luan], Liu, X.M.[Xiao-Ming],
Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction,
CVPR21(7419-7429)
IEEE DOI 2111
Training, Solid modeling, Image segmentation, Shape, Fitting 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], Saà-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], 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.[Jiri], 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

Wang, F., Yeh, Y., Sun, M., Chiu, W., Tsai, Y.,
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion,
CVPR20(459-468)
IEEE DOI 2008
Face, Estimation, Cameras, Distortion, Convolution, Neural networks 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

Paschalidou, D., Van Gool, L.J., Geiger, A.,
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects From a Single RGB Image,
CVPR20(1057-1067)
IEEE DOI 2008
Shape, Geometry, Image reconstruction, Neural networks, 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], Hašan, M.[Miloš], 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

Wiles, O., Gkioxari, G., Szeliski, R., Johnson, J.,
SynSin: End-to-End View Synthesis From a Single Image,
CVPR20(7465-7475)
IEEE DOI 2008
Semantics, Task analysis, Image resolution, Training, Solid modeling, Rendering (computer graphics) 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.[Yufei], 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

Mo, K.C.[Kai-Chun], Wang, H.[He], Yan, X.C.[Xin-Chen], Guibas, L.J.[Leonidas J.],
Pt2pc: Learning to Generate 3d Point Cloud Shapes from Part Tree Conditions,
ECCV20(VI:683-701).
Springer DOI 2011
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.[Yanchao], 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

Mandikal, P.[Priyanka], Navaneet, K.L., Babu, R.V.[R. Venkatesh],
3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction from a Single Image,
3DSemantics18(III:662-674).
Springer DOI 1905
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

Qian, Y.M.[Yi-Ming], Ramalingam, S.[Srikumar], Elder, J.H.[James H.],
LS3D: Single-View Gestalt 3D Surface Reconstruction from Manhattan Line Segments,
ACCV18(IV:399-416).
Springer DOI 1906
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

Ranade, S.[Siddhant], Ramalingam, S.[Srikumar],
Novel Single View Constraints for Manhattan 3D Line Reconstruction,
3DV18(625-633)
IEEE DOI 1812
computational geometry, game theory, graph theory, image reconstruction, integer programming, linear programming, structure from motion BibRef

Lin, H.J., Huang, S., Lai, S., Chiang, C.,
Indoor Scene Layout Estimation from a Single Image,
ICPR18(842-847)
IEEE DOI 1812
Layout, Estimation, Semantics, Training, Image edge detection, Task analysis, Pipelines 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 .