Single-Image Depth Estimation is a computational task in computer vision that infers a dense depth map from a single RGB image, distinguishing itself from multi-view approaches by relying solely on monocular visual cues and learned priors.
243
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27.8K
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736
Authors
236
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Publications per year
2017–2026
174
Parents
Publications
243
Learning Depth from Single Monocular Images
Ashutosh Saxena, Sung Heon Chung, Andrew Y. Ng · 2005 · 939 citations
1–5 of 243
Authors
736
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1–5 of 736
Institutions
236
The University of Adelaide
Adelaide, Australia
10 h-index
25 publications
9K citations
University of Bologna
Bologna, Italy
9 h-index
43 publications
2.1K citations
Tsinghua University
Beijing, China
8 h-index
22 publications
1.3K citations
Stanford University
Stanford, United States
7 h-index
20 publications
7.9K citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
7 h-index
17 publications
492 citations
Zhejiang University
Hangzhou, China
6 h-index
7 publications
454 citations
Adobe Systems (United States)
San Jose, United States
6 h-index
18 publications
2.7K citations
University of Michigan
Ann Arbor, United States
5 h-index
13 publications
772 citations
1–8 of 236
Venues
- arXiv (Cornell University)
Repository · 41 publications · 5.4K citations
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- IEEE Transactions on Image Processing
8 publications · 634 citations
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- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 6 publications · 2.6K citations
6
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- IEEE Transactions on Circuits and Systems for Video Technology
4 publications · 98 citations
4
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- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Conference · 4 publications · 487 citations
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