Self-supervised Depth Estimation
Self-Supervised Depth Estimation is a methodological framework within depth estimation that leverages unlabeled monocular video sequences to learn depth and camera pose through image reconstruction consistency, without requiring explicit ground-truth depth annotations.
256
Publications
12.2K
Citations
769
Authors
213
Institutions
Publications per year
2017–2026
255
Parents
256
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
Nan Yang, Lukas von Stumberg, Rui Wang et al. · 2020 · 411 citations
SfM-Net: Learning of Structure and Motion from Video
Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid et al. · arXiv (Cornell University) · 2017 · 354 citations · Full text
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
Mahmoud Assran, Quentin Duval, Ishan Misra et al. · 2023 · 293 citations
1–5 of 256
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213

University of Bologna
Bologna, Italy
11 h-index
36 publications
2.8K citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
10 h-index
24 publications
602 citations

Peking University
Beijing, China
9 h-index
35 publications
1.9K citations
ETH Zurich
Zurich, Switzerland
9 h-index
29 publications
2.1K citations

Shanghai Jiao Tong University
Shanghai, China
8 h-index
20 publications
588 citations
Tsinghua University
Beijing, China
8 h-index
27 publications
1.4K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
22 publications
707 citations
University of Chinese Academy of Sciences
Beijing, China
7 h-index
17 publications
451 citations
1–8 of 213
Repository · 38 publications · 1.3K citations
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Conference · 13 publications · 978 citations
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11 publications · 541 citations
13
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7 publications · 266 citations
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TPAMI · 5 publications · 179 citations
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