Ordinal Depth Estimation
Ordinal Depth Estimation is a depth estimation framework that models depth as a relative ordinal relation between pixels or regions, differing from metric depth estimation by predicting the order of depth values rather than their exact continuous magnitudes.
15
Publications
2.4K
Citations
38
Authors
20
Institutions
Publications per year
2017–2026
5
Parents
15
MegaDepth: Learning Single-View Depth Prediction from Internet Photos
Zhengqi Li, Noah Snavely · 2018 · 1.1K citations
Ordinal Depth Supervision for 3D Human Pose Estimation
Georgios Pavlakos, Xiaowei Zhou, Kostas Daniilidis · 2018 · 442 citations
Learning Ordinal Relationships for Mid-Level Vision
Daniel Zoran, Phillip Isola, Dilip Krishnan et al. · 2015 · 175 citations · Full text
Ordinal depth information from accommodation?
Mark Mon‐Williams, James R. Tresilian · Ergonomics · 2000 · 85 citations
Medicine, Psychology, Vision Science +15
1–5 of 15
38
2
h-index
2
h-index
2
h-index
1
h-index
1
h-index
1–5 of 38
20
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
3 publications
182 citations

Cornell University
Ithaca, United States
2 h-index
4 publications
2.3K citations

University of St Andrews
St Andrews, United Kingdom
2 h-index
5 publications
333 citations
Stanford University
Stanford, United States
2 h-index
6 publications
249 citations
Institute of Cognitive and Brain Sciences
New York, United States
1 h-index
1 publications
37 citations
California University of Pennsylvania
California, United States
1 h-index
2 publications
884 citations

Zhejiang University
Hangzhou, China
1 h-index
1 publications
442 citations
Google (United States)
Mountain View, United States
1 h-index
2 publications
350 citations
1–8 of 20
2 publications · 96 citations
2
h-index
TPAMI · 1 publications · 97 citations
1
h-index
1 publications · 85 citations
1
h-index
1 publications · 82 citations
1
h-index
TOG · 1 publications · 73 citations
1
h-index
1–5