9.8.1 Single Image, Single View 3D Reconstruction

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.

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

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

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

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

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

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

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

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

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, 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

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

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, 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

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

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

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.F.[Yi-Fan], 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

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

Gao, G.Q.[Guo-Qing], Yang, L.[Liang], Zhang, Q.[Quan], Wang, C.M.[Chong-Min], Bao, H.[Hua], Rao, C.H.[Chang-Hui],
ISHS-Net: Single-View 3D Reconstruction by Fusing Features of Image and Shape Hierarchical Structures,
RS(15), No. 23, 2023, pp. 5449.
DOI Link 2312
BibRef

Lei, C.[Chen], Zheng-You, L.[Liang], Yu, S.[Sun],
A monocular image depth estimation method based on weighted fusion and point-wise convolution,
IET-CV(17), No. 8, 2023, pp. 1005-1016.
DOI Link 2312
convolutional neural nets, estimation theory, image processing, indoor environment BibRef

Liu, Z.[Zhong], Li, R.[Ran], Shao, S.W.[Shu-Wei], Wu, X.M.[Xing-Ming], Chen, W.H.[Wei-Hai],
Self-Supervised Monocular Depth Estimation with Self-Reference Distillation and Disparity Offset Refinement,
CirSysVideo(33), No. 12, December 2023, pp. 7565-7577.
IEEE DOI 2312
BibRef

Lv, J.W.[Jun-Wei], Zhang, Y.T.[Yue-Ting], Guo, J.Y.[Jia-Yi], Zhao, X.[Xin], Gao, M.[Ming], Lei, B.[Bin],
Attention-Based Monocular Depth Estimation Considering Global and Local Information in Remote Sensing Images,
RS(16), No. 3, 2024, pp. 585.
DOI Link 2402
BibRef

Braun, D.[Daniel], Morel, O.[Olivier], Demonceaux, C.[Cédric], Vasseur, P.[Pascal],
N-QGNv2: Predicting the optimum quadtree representation of a depth map from a monocular camera,
PRL(179), 2024, pp. 94-100.
Elsevier DOI 2403
Deep learning, Quadtree, Compression, Sparse convolutions, Depth map, Monocular image BibRef

Arampatzakis, V.[Vasileios], Pavlidis, G.[George], Mitianoudis, N.[Nikolaos], Papamarkos, N.[Nikos],
Monocular Depth Estimation: A Thorough Review,
PAMI(46), No. 4, April 2024, pp. 2396-2414.
IEEE DOI 2403
Survey, Monocular Depth. Estimation, Visualization, Observers, Pattern analysis, Visual perception, Real-time systems, Artificial intelligence, monocular depth BibRef

Lin, X.[Xiaocan], Li, N.[Nan],
Self-supervised learning monocular depth estimation from internet photos,
JVCIR(99), 2024, pp. 104063.
Elsevier DOI 2403
Monocular depth estimation, Self-supervised learning, Internet-data-driven BibRef

Zhou, D.Z.[Da-Zheng], Zhang, M.L.[Ming-Liang], Gao, X.J.[Xian-Jie], Zhang, Y.M.[You-Mei], Li, B.[Bin],
Complete Contextual Information Extraction for Self-Supervised Monocular Depth Estimation,
CVIU(245), 2024, pp. 104032.
Elsevier DOI 2406
Monocular depth estimation, Self-supervised learning, Transformer, Convolutional neural networks BibRef

Zhu, R.J.[Rui-Jie], Song, Z.Y.[Zi-Yang], Liu, L.[Li], He, J.F.[Jian-Feng], Zhang, T.Z.[Tian-Zhu], Zhang, Y.D.[Yong-Dong],
HA-Bins: Hierarchical Adaptive Bins for Robust Monocular Depth Estimation Across Multiple Datasets,
CirSysVideo(34), No. 6, June 2024, pp. 4354-4366.
IEEE DOI 2406
Estimation, Transformers, Correlation, Decoding, Generators, Task analysis, Predictive models, Monocular depth estimation, dense prediction BibRef

Liu, L.[Li], Zhu, R.J.[Rui-Jie], Deng, J.C.[Jia-Cheng], Song, Z.Y.[Zi-Yang], Yang, W.F.[Wen-Fei], Zhang, T.Z.[Tian-Zhu],
Plane2Depth: Hierarchical Adaptive Plane Guidance for Monocular Depth Estimation,
CirSysVideo(35), No. 2, February 2025, pp. 1136-1149.
IEEE DOI 2502
Estimation, Adaptation models, Cameras, Aggregates, Predictive models, Feature extraction, dense prediction BibRef

Xian, K.[Ke], Cao, Z.G.[Zhi-Guo], Shen, C.H.[Chun-Hua], Lin, G.S.[Guo-Sheng],
Towards Robust Monocular Depth Estimation: A New Baseline and Benchmark,
IJCV(132), No. 7, July 2024, pp. Pages2401-2419.
Springer DOI 2406
BibRef

Xiang, M.[Mochu], Zhang, J.[Jing], Barnes, N.M.[Nick M.], Dai, Y.C.[Yu-Chao],
Measuring and Modeling Uncertainty Degree for Monocular Depth Estimation,
CirSysVideo(34), No. 7, July 2024, pp. 5716-5727.
IEEE DOI Code:
WWW Link. 2407
Uncertainty, Estimation, Measurement uncertainty, Predictive models, Calibration, Computational modeling, Training, uncertainty modeling BibRef

Xiang, X.Z.[Xue-Zhi], Li, W.[Wei], Wang, Y.[Yao], El Saddik, A.[Abdulmotaleb],
Self-supervised monocular depth estimation with self-distillation and dense skip connection,
CVIU(246), 2024, pp. 104048.
Elsevier DOI 2408
Monocular depth estimation, Self-supervised learning, Self-distillation, Dense skip connection BibRef

Xiang, X.Z.[Xue-Zhi], Wang, Y.[Yao], Li, X.H.[Xiao-Heng], Zhang, L.[Lei], Zhen, X.T.[Xian-Tong],
Self-supervised monocular depth estimation with large kernel attention and dynamic scene perception,
JVCIR(108), 2025, pp. 104413.
Elsevier DOI 2503
Monocular depth estimation, Self-supervised learning, Large kernel attention, Dynamic scene perception BibRef

Liu, X.[Xu], Li, J.N.[Jia-Ning], Shi, J.Q.[Jin-Qiao], Fan, X.P.[Xiao-Peng], Tian, Y.H.[Yong-Hong], Zhao, D.B.[De-Bin],
Event-Based Monocular Depth Estimation With Recurrent Transformers,
CirSysVideo(34), No. 8, August 2024, pp. 7417-7429.
IEEE DOI Code:
WWW Link. 2408
Transformers, Estimation, Cameras, Voltage control, Task analysis, Streaming media, Event camera, cross attention BibRef

Jun, J.[Jinyoung], Lee, J.H.[Jae-Han], Kim, C.S.[Chang-Su],
Versatile depth estimator based on common relative depth estimation and camera-specific relative-to-metric depth conversion,
JVCIR(103), 2024, pp. 104252.
Elsevier DOI 2409
Monocular depth estimation, Versatile depth estimation, Relative depth estimation, Camera-specific depth conversion BibRef

Chu, F.P.[Fu-Peng], Cong, Y.[Yang], Chen, R.[Ronghan],
OPEN: Occlusion-Invariant Perception Network for Single Image-Based 3D Shape Retrieval,
CirSysVideo(34), No. 9, September 2024, pp. 7998-8012.
IEEE DOI 2410
Shape, Image representation, Feature extraction, Self-supervised learning, Task analysis, Streams, consistency learning BibRef

Ignatov, D.[Dmitry], Ignatov, A.[Andrey], Timofte, R.[Radu],
Virtually Enriched NYU Depth V2 Dataset for Monocular Depth Estimation: Do We Need Artificial Augmentation?,
NTIRE24(6177-6186)
IEEE DOI Code:
WWW Link. 2410
Training, Solid modeling, Computational modeling, Estimation, Training data, Lighting, synthetic augmentation, monocular depth estimation BibRef

Shao, S.W.[Shu-Wei], Pei, Z.C.[Zhong-Cai], Chen, W.H.[Wei-Hai], Chen, P.C.Y.[Peter C. Y.], Li, Z.G.[Zheng-Guo],
NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion,
PAMI(46), No. 12, December 2024, pp. 8883-8899.
IEEE DOI 2411
Estimation, Head, Magnetic heads, Deep learning, Vectors, Uncertainty, Monocular depth estimation, depth completion, surface normal, piece-wise planar constraint BibRef

Shao, S.W.[Shu-Wei], Pei, Z.C.[Zhong-Cai], Chen, W.H.[Wei-Hai], Wu, X.M.[Xing-Ming], Li, Z.G.[Zheng-Guo],
NDDepth: Normal-Distance Assisted Monocular Depth Estimation,
ICCV23(7897-7906)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gao, Y.B.[Yan-Bo], Wu, X.Y.[Xian-Ye], Li, S.[Shuai], Cai, X.[Xun], Li, C.K.[Chuan-Kun],
Color and Geometric Contrastive Learning Based Intra-Frame Supervision for Self-Supervised Monocular Depth Estimation,
SPLetters(31), 2024, pp. 2940-2944.
IEEE DOI 2411
Estimation, Image color analysis, Contrastive learning, Decoding, Feature extraction, Transformers, Color, Vectors, self-supervised learning BibRef

Wang, C.H.[Chang-Hao], Zhang, G.W.[Guan-Wen], Cheng, Z.Y.[Zheng-Yun], Zhou, W.[Wei],
MonoBooster: Semi-Dense Skip Connection With Cross-Level Attention for Boosting Self-Supervised Monocular Depth Estimation,
SPLetters(31), 2024, pp. 3069-3073.
IEEE DOI 2411
Convolution, Feature extraction, Indexes, Aggregates, Data mining, Accuracy, Transformers, Fuses, skip connection BibRef

Zhou, Z.K.[Zhong-Kai], Fan, X.[Xinnan], Shi, P.F.[Peng-Fei], Xin, Y.Y.X.[Yuan-Yan-Xue], Duan, D.L.[Dong-Liang], Yang, L.Q.[Liu-Qing],
Recurrent Multiscale Feature Modulation for Geometry Consistent Depth Learning,
PAMI(46), No. 12, December 2024, pp. 9551-9566.
IEEE DOI 2411
Estimation, Geometry, Training, Accuracy, Task analysis, Cameras, Geometry consistency, lightweight, monocular depth estimation, self-supervised learning BibRef

Papa, L.[Lorenzo], Russo, P.[Paolo], Amerini, I.[Irene],
D4D: An RGBD Diffusion Model to Boost Monocular Depth Estimation,
CirSysVideo(34), No. 10, October 2024, pp. 9852-9865.
IEEE DOI 2411
Training, Task analysis, Pipelines, Data models, Estimation, Computational modeling, generation BibRef

Hou, S.Y.[Sheng-Yu], Fu, M.Y.[Meng-Yin], Wang, R.C.[Rong-Chuan], Yang, Y.[Yi], Song, W.J.[Wen-Jie],
Self-Supervised Monocular Depth Estimation for All-Day Images Based on Dual-Axis Transformer,
CirSysVideo(34), No. 10, October 2024, pp. 9939-9953.
IEEE DOI 2411
Estimation, Lighting, Transformers, Adaptation models, Light sources, Training, Monocular depth estimation, transformer network BibRef

Hu, H.J.[Heng-Jia], Liang, M.N.[Meng-Nan], Wang, C.C.[Cong-Cong], Zhao, M.[Meng], Shi, F.[Fan], Zhang, C.[Chao], Han, Y.L.[Yi-Lin],
Monocular depth estimation with boundary attention mechanism and Shifted Window Adaptive Bins,
CVIU(249), 2024, pp. 104220.
Elsevier DOI 2412
Monocular depth estimation, Attention mechanism, Adaptive bins, Convolutional neural networks BibRef

Liu, C.[Cong], Zhang, C.[Chaobo], Liang, X.J.[Xiao-Jun], Han, Z.M.[Zhi-Ming], Li, Y.M.[Yi-Ming], Yang, C.H.[Chun-Hua], Gui, W.H.[Wei-Hua], Gao, W.[Wen], Wang, X.H.[Xiao-Hao], Li, X.H.[Xing-Hui],
Attention Mono-Depth: Attention-Enhanced Transformer for Monocular Depth Estimation of Volatile Kiln Burden Surface,
CirSysVideo(35), No. 2, February 2025, pp. 1686-1699.
IEEE DOI Code:
WWW Link. 2502
Kilns, Transformers, Feature extraction, Estimation, Head, Accuracy, Temperature distribution, Surface treatment, attention mechanism BibRef

Feng, C.[Cheng], Zhang, C.X.[Cong-Xuan], Chen, Z.[Zhen], Hu, W.M.[Wei-Ming], Lu, K.[Ke], Ge, L.[Liyue],
Self-Supervised Monocular Depth Estimation With Dual-Path Encoders and Offset Field Interpolation,
IP(34), 2025, pp. 939-954.
IEEE DOI 2502
BibRef
Earlier: A1, A2, A3, A4, A6, Only:
Real-Time Monocular Depth Estimation on Embedded Systems,
ICIP24(3464-3470)
IEEE DOI 2411
Depth measurement, Accuracy, Feature extraction, Interpolation, Costs, Estimation, Cameras, Training, Decoding, Data models, self-supervised. Accuracy, Runtime, Estimation, Network architecture, Robot sensing systems, Real-time systems, Depth Estimation BibRef

Zhang, J.[Jiehua], Li, L.[Liang], Yan, C.G.[Cheng-Gang], Ke, W.[Wei], Gong, Y.H.[Yi-Hong],
Monocular Depth Estimation on Adverse Weathers With Curriculum Domain Distribution Alignment,
CirSysVideo(35), No. 1, January 2025, pp. 178-194.
IEEE DOI 2502
Meteorology, Estimation, Training, Adaptation models, Data models, Bridge circuits, adverse weathers BibRef

Wu, L.[Liehao], Wang, L.[Laihua], Wei, G.H.[Guang-Hui], Yu, Y.[Yang],
HPD-Depth: High performance decoding network for self-supervised monocular depth estimation,
IVC(154), 2025, pp. 105360.
Elsevier DOI 2502
Self-supervision, Multi-scale feature fusion, High performance decoding, Monocular depth estimation BibRef

Sun, B.[Bo], Kang, H.[Hao], Guan, L.[Li], Li, H.X.[Hao-Xiang], Mordohai, P.[Philippos], Hua, G.[Gang],
Glissando-Net: Deep Single View Category Level Pose Estimation and 3D Reconstruction,
PAMI(47), No. 4, April 2025, pp. 2298-2312.
IEEE DOI 2503
Shape, Point cloud compression, Solid modeling, Training, Decoding, Pose estimation, Image reconstruction, Predictive models, variational autoencoder BibRef

Yu, S.S.[Shang-Shu], Wu, M.Q.[Mei-Qing], Lam, S.K.[Siew-Kei], Wang, C.S.[Chang-Shuo], Wang, R.P.[Rui-Ping],
EDS-Depth: Enhancing Self-Supervised Monocular Depth Estimation in Dynamic Scenes,
ITS(26), No. 4, April 2025, pp. 5585-5597.
IEEE DOI 2504
Dynamics, Vehicle dynamics, Depth measurement, Training, Cameras, Semantics, Motion segmentation, Accuracy, Optical flow, dynamic scenes BibRef

Shao, S.W.[Shu-Wei], Pei, Z.[Zhongcai], Chen, W.H.[Wei-Hai], Sun, D.[Dingchi], Chen, P.C.Y.[Peter C. Y.], Li, Z.G.[Zheng-Guo],
MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model,
CirSysVideo(35), No. 4, April 2025, pp. 3664-3678.
IEEE DOI 2504
Diffusion models, Noise reduction, Training, Accuracy, Standards, Diffusion processes, Visualization, self-supervised learning BibRef

Guo, H.Y.[Hao-Yu], Li, Y.[Ying], Deng, C.Y.[Chun-Yan],
TLR-3DRN: Unsupervised single-view reconstruction via tri-layer renderer,
PR(164), 2025, pp. 111568.
Elsevier DOI 2504
Single-view reconstruction, Unsupervised learning BibRef

Jhang, J.C.[Jin-Cheng], Tu, T.[Tao], Wang, F.E.[Fu-En], Zhang, K.[Ke], Sun, M.[Min], Kuo, C.H.[Cheng-Hao],
V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations,
WACV25(9577-9586)
IEEE DOI 2505
Training, Point cloud compression, Annotations, Depth measurement, Refining, Training data, Object detection, Detectors, Cameras, indoor BibRef

Li, J.H.[Jian-Hao], Sun, T.Y.[Tian-Yu], Wang, Z.[Zhongdao], Xie, E.[Enze], Feng, B.[Bailan], Zhang, H.B.[Hong-Bo], Yuan, Z.[Ze], Xu, K.[Ke], Liu, J.H.[Jia-Heng], Luo, P.[Ping],
Segment, Lift and Fit: Automatic 3d Shape Labeling from 2d Prompts,
ECCV24(LXXXIV: 407-423).
Springer DOI 2412
BibRef

Yu, W.B.[Wang-Bo], Yuan, L.[Li], Cao, Y.P.[Yan-Pei], Gao, X.J.[Xiang-Jun], Li, X.Y.[Xiao-Yu], Hu, W.B.[Wen-Bo], Quan, L.[Long], Shan, Y.[Ying], Tian, Y.H.[Yong-Hong],
HIFI-123: Towards High-fidelity One Image to 3d Content Generation,
ECCV24(LXXIII: 258-274).
Springer DOI 2412
Project:
WWW Link. BibRef

Shen, Q.H.[Qiu-Hong], Yang, X.Y.[Xing-Yi], Mi, M.B.[Michael Bi], Wang, X.C.[Xin-Chao],
Vista3d: Unravel the 3d Darkside of a Single Image,
ECCV24(XXII: 405-421).
Springer DOI 2412
Code:
WWW Link. BibRef

Liu, J.F.[Jin-Feng], Kong, L.T.[Ling-Tong], Li, B.[Bo], Wang, Z.R.[Ze-Rong], Gu, H.[Hong], Chen, J.[Jinwei],
Mono-VIFI: A Unified Learning Framework for Self-supervised Single and Multi-frame Monocular Depth Estimation,
ECCV24(XLV: 90-107).
Springer DOI 2412
BibRef

Jia, D.[Dian], Ruan, X.Q.[Xiao-Qian], Xia, K.[Kun], Zou, Z.M.[Zhi-Ming], Wang, L.[Le], Tang, W.[Wei],
Analysis-by-Synthesis Transformer for Single-View 3d Reconstruction,
ECCV24(XXI: 259-277).
Springer DOI 2412
BibRef

Schön, M.[Markus], Buchholz, M.[Michael], Dietmayer, K.[Klaus],
MGNICENET: Unified Monocular Geometric Scene Understanding,
ACCV24(VIII: 332-350).
Springer DOI 2412
Code:
WWW Link. BibRef

Li, Z.Y.[Zhen-Yu], Bhat, S.F.[Shariq Farooq], Wonka, P.[Peter],
Patchrefiner: Leveraging Synthetic Data for Real-domain High-resolution Monocular Metric Depth Estimation,
ECCV24(LXVII: 250-267).
Springer DOI 2412
BibRef

Fu, X.[Xiao], Yin, W.[Wei], Hu, M.[Mu], Wang, K.X.[Kai-Xuan], Ma, Y.X.[Yue-Xin], Tan, P.[Ping], Shen, S.J.[Shao-Jie], Lin, D.[Dahua], Long, X.X.[Xiao-Xiao],
Geowizard: Unleashing the Diffusion Priors for 3d Geometry Estimation from a Single Image,
ECCV24(XXII: 241-258).
Springer DOI 2412
BibRef

Duan, Y.Q.[Yi-Quan], Guo, X.[Xianda], Zhu, Z.[Zheng],
Diffusiondepth: Diffusion Denoising Approach for Monocular Depth Estimation,
ECCV24(XI: 432-449).
Springer DOI 2412
BibRef

Tosi, F.[Fabio], Ramirez, P.Z.[Pierluigi Zama], Poggi, M.[Matteo],
Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions,
ECCV24(XXIII: 236-257).
Springer DOI 2412
BibRef

Lao, D.[Dong], Yang, F.Y.[Feng-Yu], Wang, D.[Daniel], Park, H.[Hyoungseob], Lu, S.[Samuel], Wong, A.[Alex], Soatto, S.[Stefano],
On the Viability of Monocular Depth Pre-Training for Semantic Segmentation,
ECCV24(XXXVII: 340-357).
Springer DOI 2412
BibRef

Zhang, J.[Junwu], Tang, Z.Y.[Zhen-Yu], Pang, Y.[Yatian], Cheng, X.H.[Xin-Hua], Jin, P.[Peng], Wei, Y.[Yida], Zhou, X.[Xing], Ning, M.[Munan], Yuan, L.[Li],
Repaint123: Fast and High-quality One Image to 3d Generation with Progressive Controllable Repainting,
ECCV24(XXV: 303-320).
Springer DOI 2412
BibRef

Voleti, V.[Vikram], Yao, C.H.[Chun-Han], Boss, M.[Mark], Letts, A.[Adam], Pankratz, D.[David], Tochilkin, D.[Dmitry], Laforte, C.[Christian], Rombach, R.[Robin], Jampani, V.[Varun],
SV3D: Novel Multi-view Synthesis and 3d Generation from a Single Image Using Latent Video Diffusion,
ECCV24(I: 439-457).
Springer DOI 2412
BibRef

Chen, Y.[Yabo], Fang, J.[Jiemin], Huang, Y.Y.[Yu-Yang], Yi, T.[Taoran], Zhang, X.P.[Xiao-Peng], Xie, L.X.[Ling-Xi], Wang, X.G.[Xing-Gang], Dai, W.R.[Wen-Rui], Xiong, H.K.[Hong-Kai], Tian, Q.[Qi],
Cascade-Zero123: One Image to Highly Consistent 3d with Self-prompted Nearby Views,
ECCV24(XLI: 311-330).
Springer DOI 2412
BibRef

Han, W.C.[Wen-Cheng], Shen, J.B.[Jian-Bing],
High-precision Self-supervised Monocular Depth Estimation with Rich-resource Prior,
ECCV24(XXXI: 146-162).
Springer DOI 2412
BibRef

Zavadski, D.[Denis], Kalšan, D.[Damjan], Rother, C.[Carsten],
Primedepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage,
ACCV24(V: 21-40).
Springer DOI 2412
BibRef

Zhang, X.[Xidan], Wei, J.N.[Jia-Ning], Moteki, A.[Atsunori], Kobayashi, Y.[Yoshie], Suzuki, G.[Genta], Tan, Z.M.[Zhi-Ming],
MSD-CRFS: Multi-Scale Dual Aggregation Conditional Random Fields for Monocular Depth Estimation,
ICIP24(2001-2007)
IEEE DOI 2411
Measurement, Geometry, Attention mechanisms, Accuracy, Fuses, Estimation, monocular depth estimation, conditional random field, multi-scale BibRef

Friday, S.[Sarah], Shi, Y.Z.[Yun-Zi], Cherivirala, Y.[Yaswanth], Saragadam, V.[Vishwanath], Pediredla, A.[Adithya],
Snapshot Lidar: Fourier Embedding of Amplitude and Phase for Single-Image Depth Reconstruction,
CVPR24(25203-25212)
IEEE DOI 2410
Geometry, Time-frequency analysis, Laser radar, Robot vision systems, Imaging, Prototypes, Cameras BibRef

Yi, X.Y.[Xuan-Yu], Wu, Z.[Zike], Xu, Q.S.[Qing-Shan], Zhou, P.[Pan], Lim, J.H.[Joo-Hwee], Zhang, H.W.[Han-Wang],
Diffusion Time-step Curriculum for One Image to 3D Generation,
CVPR24(9948-9958)
IEEE DOI Code:
WWW Link. 2410
Solid modeling, Codes, Computational modeling, Pipelines, Diffusion models, 3D Generation BibRef

Long, X.X.[Xiao-Xiao], Guo, Y.C.[Yuan-Chen], Lin, C.[Cheng], Liu, Y.[Yuan], Dou, Z.Y.[Zhi-Yang], Liu, L.J.[Ling-Jie], Ma, Y.X.[Yue-Xin], Zhang, S.H.[Song-Hai], Habermann, M.[Marc], Theobalt, C.[Christian], Wang, W.P.[Wen-Ping],
Wonder3D: Single Image to 3D Using Cross-Domain Diffusion,
CVPR24(9970-9980)
IEEE DOI 2410
Geometry, Surface reconstruction, Color, Diffusion models, 3D generation, diffusion, normal, MVS, NeuS BibRef

Li, Z.Y.[Zhen-Yu], Bhat, S.F.[Shariq Farooq], Wonka, P.[Peter],
PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation,
CVPR24(10016-10025)
IEEE DOI 2410
Training, Image resolution, Fuses, Computational modeling, Estimation, Network architecture BibRef

Nguyen, H.C.[Hoang Chuong], Wang, T.Y.[Tian-Yu], Alvarez, J.M.[Jose M.], Liu, M.M.[Miao-Miao],
Mining Supervision for Dynamic Regions in Self-Supervised Monocular Depth Estimation,
CVPR24(10446-10455)
IEEE DOI Code:
WWW Link. 2410
Training, Motion estimation, Dynamics, Pipelines, Estimation, Training data, Reliability BibRef

Talker, L.[Lior], Cohen, A.[Aviad], Yosef, E.[Erez], Dana, A.[Alexandra], Dinerstein, M.[Michael],
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimation,
CVPR24(10606-10616)
IEEE DOI 2410
Training, Location awareness, Accuracy, Image edge detection, Refining, Estimation, Monocular Depth Estimation, Depth Edges, Occlusion Boundaries BibRef

Ke, B.X.[Bing-Xin], Obukhov, A.[Anton], Huang, S.[Shengyu], Metzger, N.[Nando], Daudt, R.C.[Rodrigo Caye], Schindler, K.[Konrad],
Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation,
CVPR24(9492-9502)
IEEE DOI Code:
WWW Link. 2410
Training, Visualization, Computational modeling, Estimation, Training data, depth estimation, diffusion, LDM, ddpm, ddim, vision, generative BibRef

Varma, T.M.[T. Mukund], Wang, P.H.[Pei-Hao], Fan, Z.W.[Zhi-Wen], Wang, Z.Y.[Zhang-Yang], Su, H.[Hao], Ramamoorthi, R.[Ravi],
Lift3D: Zero-Shot Lifting of Any 2D Vision Model to 3D,
CVPR24(21367-21377)
IEEE DOI 2410
Training, Solid modeling, Visualization, Vocabulary, Semantic segmentation, Computational modeling BibRef

Xu, J.[Jimin], Wang, T.B.[Tian-Bao], Jin, T.[Tao], Zhang, S.Y.[Sheng-Yu], Fu, D.J.[Dong-Jie], Wang, Z.[Zhe], Lyu, J.J.[Jiang-Jing], Lv, C.F.[Cheng-Fei], Niu, C.Y.[Chao-Yue], Yu, Z.[Zhou], Zhao, Z.[Zhou], Wu, F.[Fei],
MPOD123: One Image to 3D Content Generation Using Mask-Enhanced Progressive Outline-to-Detail Optimization,
CVPR24(10682-10692)
IEEE DOI 2410
Geometry, Shape, Propulsion, Benchmark testing, Diffusion models, 3D Content Generation BibRef

Chatterjee, A.[Agneet], Gokhale, T.[Tejas], Baral, C.[Chitta], Yang, Y.Z.[Ye-Zhou],
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation,
CVPR24(2794-2803)
IEEE DOI Code:
WWW Link. 2410
With added language prompts. Natural languages, Semantics, Estimation, Benchmark testing, Robustness, Low-level vision BibRef

Oh, W.[Wonseok], Jo, Y.[Youngjoo],
From 2D Portraits to 3D Realities: Advancing GAN Inversion for Enhanced Image Synthesis,
L3D24(737-746)
IEEE DOI 2410
Visualization, Image synthesis, Computational modeling, Semantics, Aerospace electronics, Generative adversarial networks, GAN Inversion BibRef

Dana, A.[Alexandra], Carmel, N.[Nadav], Shomer, A.[Amit], Manela, O.[Ofer], Peleg, T.[Tomer],
Do More With What You Have: Transferring Depth-Scale from Labeled to Unlabeled Domains,
WAD24(4440-4450)
IEEE DOI 2410
Training, Image sensors, Accuracy, Predictive models, Cameras, Monocular depth estimation, domain adaptation BibRef

Patni, S.[Suraj], Agarwal, A.[Aradhye], Arora, C.[Chetan],
ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimation,
CVPR24(28285-28295)
IEEE DOI 2410
Codes, Pipelines, Estimation, Benchmark testing, Diffusion models, monocular-depth-estimation, stable-diffusion-backbone BibRef

Hu, H.Z.[Han-Zhe], Zhou, Z.[Zhizhuo], Jampani, V.[Varun], Tulsiani, S.[Shubham],
MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation,
CVPR24(9698-9707)
IEEE DOI 2410
Geometry, Solid modeling, Accuracy, Noise reduction, Diffusion models BibRef

Wang, Y.Z.[Yi-Zhi], Lira, W.[Wallace], Wang, W.Q.[Wen-Qi], Mahdavi-Amiri, A.[Ali], Zhang, H.[Hao],
Slice3D: Multi-Slice, Occlusion-Revealing, Single View 3D Reconstruction,
CVPR24(9881-9891)
IEEE DOI 2410
Solid modeling, Shape, Noise reduction, Graphics processing units, Predictive models, Transformers, Single View 3D Reconstruction, 3D Generation BibRef

Corona-Figueroa, A.[Abril], Shum, H.P.H.[Hubert P. H.], Willcocks, C.G.[Chris G.],
Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modeling,
EnhanceMedIm24(2315-2324)
IEEE DOI 2410
Training, Solid modeling, Uncertainty, Encoding, Iterative methods, 2D to 3D image translation, X-ray to CT-like reconstruction BibRef

Chen, R.Y.[Rui-Yang], Yin, M.[Mohan], Shen, J.W.[Jia-Wei], Ma, W.[Wei],
Recon3D: High Quality 3D Reconstruction from a Single Image Using Generated Back-View Explicit Priors,
NRend24(2802-2811)
IEEE DOI 2410
Point cloud compression, Geometry, Solid modeling, Rendering (computer graphics) BibRef

Tschernezki, V.[Vadim], Laina, I.[Iro], Larlus, D.[Diane], Vedaldi, A.[Andrea],
Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations,
3DV22(443-453)
IEEE DOI Code:
WWW Link. 2408
Image segmentation, Semantics, Manuals, Feature extraction, Rendering (computer graphics), Task analysis, neural rendering, semantic fusion BibRef

Chen, Y.X.[Yi-Xin], Ni, J.F.[Jun-Feng], Jiang, N.[Nan], Zhang, Y.W.[Yao-Wei], Zhu, Y.X.[Yi-Xin], Huang, S.Y.[Si-Yuan],
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture,
3DV24(1456-1467)
IEEE DOI 2408
Solid modeling, Surface reconstruction, Shape, Image color analysis, Estimation, Rendering (computer graphics) BibRef

Ma, W.C.[Wen-Chao], Tan, B.[Bin], Xue, N.[Nan], Wu, T.F.[Tian-Fu], Zheng, X.W.[Xian-Wei], Xia, G.S.[Gui-Song],
HoW-3D: Holistic 3D Wireframe Perception from a Single Image,
3DV22(596-605)
IEEE DOI 2408
Geometry, Solid modeling, Image segmentation, Computational modeling, Machine vision, Benchmark testing, Geometric Deep Learning BibRef

Hu, X.T.[Xue-Ting], Zhang, C.[Ce], Zhang, Y.[Yi], Hai, B.[Bowen], Yu, K.[Ke], He, Z.H.[Zhi-Hai],
Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation,
WACV24(5582-5591)
IEEE DOI 2404
Training, Adaptation models, Visualization, Costs, Semantics, Data preprocessing, Estimation, Algorithms BibRef

Dang, Y.Y.[Yuan-Yuan], Li, C.X.[Chen-Xi], Zhang, L.J.[Li-Jie], Gao, Y.[Yu],
RCCNet: Reducing Channel Convolution Network for Monocular Depth Estimation,
CVIDL23(1-4)
IEEE DOI 2403
Deep learning, Visualization, Costs, Convolution, Computational modeling, Monocular depth estimation BibRef

Chen, R.Y.[Rong-Yu], Yang, L.L.[Lin-Lin], Yao, A.[Angela],
MHEntropy: Entropy Meets Multiple Hypotheses for Pose and Shape Recovery,
ICCV23(14794-14803)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, G.K.[Guang-Kai], Yin, W.[Wei], Chen, H.[Hao], Shen, C.H.[Chun-Hua], Cheng, K.[Kai], Zhao, F.[Feng],
FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models,
ICCV23(9276-9286)
IEEE DOI Code:
WWW Link. 2401
Refining monocular description BibRef

Saunders, K.[Kieran], Vogiatzis, G.[George], Manso, L.J.[Luis J.],
Self-supervised Monocular Depth Estimation: Let's Talk About The Weather,
ICCV23(8873-8883)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, Y.G.[Yu-Guang], Wang, K.[Kai], Li, H.[Hui], Rhee, S.M.[Seon-Min], Han, S.[Seungju], Kim, J.[Jihye], Yang, M.[Min], Yang, R.[Ran], Zhu, F.[Feng],
CORE: Co-planarity Regularized Monocular Geometry Estimation with Weak Supervision,
ICCV23(8762-8771)
IEEE DOI 2401
BibRef

Han, W.C.[Wen-Cheng], Yin, J.[Junbo], Shen, J.B.[Jian-Bing],
Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Network,
ICCV23(8579-8589)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gasperini, S.[Stefano], Morbitzer, N.[Nils], Jung, H.J.[Hyun-Jun], Navab, N.[Nassir], Tombari, F.[Federico],
Robust Monocular Depth Estimation under Challenging Conditions,
ICCV23(8143-8152)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, X.D.[Xiao-Dong], Ma, Z.[Zhuang], Ji, Z.Y.[Zhi-Yu], Ren, Z.[Zhe],
GEDepth: Ground Embedding for Monocular Depth Estimation,
ICCV23(12673-12681)
IEEE DOI 2401
BibRef

Zhou, Z.M.[Zheng-Ming], Dong, Q.[Qiulei],
Two-in-One Depth: Bridging the Gap Between Monocular and Binocular Self-supervised Depth Estimation,
ICCV23(9377-9387)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yin, W.[Wei], Zhang, C.[Chi], Chen, H.[Hao], Cai, Z.P.[Zhi-Peng], Yu, G.[Gang], Wang, K.X.[Kai-Xuan], Chen, X.Z.[Xiao-Zhi], Shen, C.H.[Chun-Hua],
Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image,
ICCV23(9009-9019)
IEEE DOI Code:
WWW Link. 2401
BibRef

Shi, J.J.[Jing-Jia], Zhi, S.F.[Shuai-Feng], Xu, K.[Kai],
PlaneRecTR: Unified Query Learning for 3D Plane Recovery from a Single View,
ICCV23(9343-9352)
IEEE DOI Code:
WWW Link. 2401
BibRef

Arshad, M.S.[Mohammad Samiul], Beksi, W.J.[William J.],
LIST: Learning Implicitly from Spatial Transformers for Single-View 3D Reconstruction,
ICCV23(9287-9296)
IEEE DOI 2401
BibRef

Rodríguez-Puigvert, J.[Javier], Batlle, V.M.[Víctor M.], Montiel, J.M.M., Martinez-Cantin, R.[Ruben], Fua, P.[Pascal], Tardós, J.D.[Juan D.], Civera, J.[Javier],
LightDepth: Single-View Depth Self-Supervision from Illumination Decline,
ICCV23(21216-21226)
IEEE DOI 2401
BibRef

Diana-Albelda, C.[Cecilia], Pérez-Villar, J.I.B.[Juan Ignacio Bravo], Montalvo, J.[Javier], García-Martín, Á.[Álvaro], Cano, J.B.[Jesús Bescós],
Self-supervised Monocular Depth Estimation on Unseen Synthetic Cameras,
CIARP23(I:449-463).
Springer DOI 2312
BibRef

Theiner, J.[Jonas], Nommensen, N.[Nils], Rhotert, J.[Jim], Springstein, M.[Matthias], Müller-Budack, E.[Eric], Ewerth, R.[Ralph],
Analyzing Results of Depth Estimation Models with Monocular Criteria,
XAI4CV23(3739-3743)
IEEE DOI 2309
BibRef

Li, W.Y.[Wei-Yu], Chen, X.L.[Xue-Lin], 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

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], Tosi, F.[Fabio], Poggi, M.[Matteo], Arora, R.S.[Ripudaman Singh], Russell, C.[Chris], Hadfield, S.[Simon], Bowden, R.[Richard], Zhou, G.Y.[Guang-Yuan], Li, Z.X.[Zheng-Xin], Rao, Q.[Qiang], Bao, Y.P.[Yi-Ping], Liu, X.[Xiao], Kim, D.[Dohyeong], Kim, J.[Jinseong], Kim, M.[Myunghyun], Lavreniuk, M.[Mykola], Li, R.[Rui], Mao, Q.[Qing], Wu, J.[Jiang], Zhu, Y.[Yu], Sun, J.Q.[Jin-Qiu], Zhang, Y.N.[Yan-Ning], Patni, S.[Suraj], Agarwal, A.[Aradhye], Arora, C.[Chetan], Sun, P.[Pihai], Jiang, K.[Kui], Wu, G.[Gang], Liu, J.[Jian], Liu, X.M.[Xian-Ming], Jiang, J.J.[Jun-Jun], Zhang, X.[Xidan], Wei, J.N.[Jia-Ning], Wang, F.[Fangjun], Tan, Z.M.[Zhi-Ming], Wang, J.[Jiabao], Luginov, A.[Albert], Shahzad, M.[Muhammad], Hosseini, S.[Seyed], Trajcevski, A.[Aleksander], Elder, J.H.[James H.],
The Third Monocular Depth Estimation Challenge,
CVPRWS24(1-14)
IEEE DOI 2410
Computational modeling, Estimation, Pattern recognition 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.M.[Jian-Mian], 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.K.[Guang-Kai], 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

Shi, X.P.[Xue-Peng], Dikov, G.[Georgi], Reitmayr, G.[Gerhard], Kim, T.K.[Tae-Kyun], Ghafoorian, M.[Mohsen],
3D Distillation: Improving Self-Supervised Monocular Depth Estimation on Reflective Surfaces,
ICCV23(9099-9109)
IEEE DOI 2401
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

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

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

Xing, Z.[Zhen], Li, H.D.[Heng-Duo], Wu, Z.X.[Zu-Xuan], 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

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

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

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

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, 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), 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, Decoding, Computational complexity, 3D from single images, Robot vision BibRef

Mohadikar, P.[Payal], Duan, Y.[Ye],
OmniDiffusion: Reformulating 360 Monocular Depth Estimation Using Semantic and Surface Normal Conditioned Diffusion,
WACV25(8068-8078)
IEEE DOI 2505
Visualization, Depth measurement, Semantic segmentation, Noise reduction, Semantics, Merging, Transformers, Iterative methods, Surface treatment 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, 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, Benchmark testing, 3D from single images, Scene analysis and understanding 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

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

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.F.[Ye-Fan], 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

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, Wavelet analysis, Decoding, Pattern recognition 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

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

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], 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.Y.[Zi-Yu], 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
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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

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

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

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
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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
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Goel, S.[Shubham], Kanazawa, A.[Angjoo], Malik, J.[Jitendra],
Shape and Viewpoint Without Keypoints,
ECCV20(XV:88-104).
Springer DOI 2011
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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

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

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

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
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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
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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, Pattern recognition 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., Ambrus, 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

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], 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

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
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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

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

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

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
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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
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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
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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

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

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

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

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

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.P.[Anders P.],
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

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
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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

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

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

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

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

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

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

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, Solid modeling, random projection 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

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

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, Learning .