Classical Optical Flow
Classical Optical Flow is a foundational methodology in computer vision that estimates pixel-wise motion between consecutive image frames by solving the optical flow constraint equation under assumptions of brightness constancy and spatial smoothness.
41
Publications
5.8K
Citations
105
Authors
53
Institutions
Publications per year
2017–2026
11
Parents
41
Secrets of optical flow estimation and their principles
Deqing Sun, Stefan Roth, Michael J. Black · 2010 · 1.4K citations
Optical Flow Estimation Using a Spatial Pyramid Network
Anurag Ranjan, Michael J. Black · 2017 · 1.4K citations
1–5 of 41
105
Max Planck Institute for Intelligent Systems, Germany
4 publications · 3.4K citations
4
h-index
3
h-index
2
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 184 citations
2
h-index
2
h-index
1–5 of 105
53
Max Planck Institute for Intelligent Systems
Stuttgart, Germany
3 h-index
5 publications
3.4K citations

Johns Hopkins University
Baltimore, United States
3 h-index
6 publications
200 citations
Institut für Informationsverarbeitung
Berlin, Germany
2 h-index
2 publications
529 citations

University of British Columbia
Vancouver, Canada
2 h-index
4 publications
655 citations

Technische Universität Darmstadt
Darmstadt, Germany
2 h-index
2 publications
2K citations

Hospital de Sant Pau
Barcelona, Spain
1 h-index
2 publications
24 citations
Nissan (United States)
Farmington Hills, United States
1 h-index
1 publications
43 citations

University of Alabama at Birmingham
Birmingham, United States
1 h-index
3 publications
579 citations
1–8 of 53
3 publications · 271 citations
3
h-index
2 publications · 105 citations
2
h-index
2 publications · 736 citations
2
h-index
2 publications · 238 citations
2
h-index
CVIU · 2 publications · 63 citations
2
h-index
1–5