Multi-view Depth Estimation
Multi-View Depth Estimation is a computational method in computer vision that infers depth information for a scene by jointly analyzing multiple images captured from distinct but overlapping viewpoints, leveraging geometric correspondences and photometric consistency across views.
226
Publications
20.9K
Citations
713
Authors
246
Institutions
Publications per year
2017–2026
150
Parents
226
Unsupervised Learning of Depth and Ego-Motion from Video
Tinghui Zhou, Matthew Brown, Noah Snavely et al. · 2017 · 2.8K citations
MegaDepth: Learning Single-View Depth Prediction from Internet Photos
Zhengqi Li, Noah Snavely · 2018 · 1.1K citations
1–5 of 226
713
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246

Huazhong University of Science and Technology
Wuhan, China
11 h-index
28 publications
2.2K citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
24 publications
1.6K citations
ETH Zurich
Zurich, Switzerland
8 h-index
14 publications
1.1K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
26 publications
714 citations
University of California, Berkeley
Berkeley, United States
6 h-index
11 publications
5.6K citations
University of California San Diego
San Diego, United States
5 h-index
14 publications
2.3K citations
Columbia University
New York, United States
5 h-index
5 publications
854 citations

Beihang University
Beijing, China
5 h-index
20 publications
956 citations
1–8 of 246
Repository · 25 publications · 950 citations
18
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TPAMI · 12 publications · 2.8K citations
11
h-index
11 publications · 407 citations
11
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Conference · 8 publications · 540 citations
8
h-index
Conference · 7 publications · 1.1K citations
7
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1–5