Disparity-driven Depth Perception
Disparity-Driven Depth Perception is a computational framework in visual neuroscience and computer vision that utilizes binocular disparity as the primary cue to infer three-dimensional scene structure, distinguishing itself from other depth perception mechanisms by explicitly relying on the geometric differences between left and right eye views to compute depth.
379
Publications
21.8K
Citations
741
Authors
290
Institutions
Publications per year
2017–2026
41
Parents
379
1–5 of 379
741
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290
University of Oxford
Oxford, United Kingdom
22 h-index
60 publications
5.3K citations
University of California, Berkeley
Berkeley, United States
19 h-index
45 publications
2.9K citations

York University
Toronto, Canada
16 h-index
53 publications
1.6K citations

University of St Andrews
St Andrews, United Kingdom
13 h-index
24 publications
773 citations
Utrecht University
Utrecht, The Netherlands
12 h-index
27 publications
973 citations
Massachusetts Institute of Technology
Cambridge, United States
12 h-index
27 publications
1.2K citations
Harvard University
Cambridge, United States
11 h-index
15 publications
2.1K citations
The University of Osaka
Osaka, Japan
11 h-index
32 publications
1.8K citations
1–8 of 290
35 publications · 3.5K citations
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46 publications · 1.9K citations
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37 publications · 1.2K citations
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37 publications · 1.7K citations
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JN · 18 publications · 2.4K citations
16
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