Sparse View Synthesis
Sparse View Synthesis is a computational method in image-based rendering that generates novel views of a scene from a limited set of input images by leveraging geometric and photometric priors to compensate for large inter-view disparities and occlusions.
45
Publications
17K
Citations
171
Authors
68
Institutions
Publications per year
2017–2026
37
Parents
45
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik et al. · Communications of the ACM · 2021 · 5.8K citations · Full text
3D Gaussian Splatting for Real-Time Radiance Field Rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler et al. · ACM Transactions on Graphics · 2023 · 4.5K citations · Full text
pixelNeRF: Neural Radiance Fields from One or Few Images
Alex Yu, Vickie Ye, Matthew Tancik et al. · 2021 · 1.4K citations
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Berkeley College
New York, United States
4 h-index
18 publications
36.8K citations
Google (United States)
Mountain View, United States
4 h-index
22 publications
10.3K citations
University of California, Berkeley
Berkeley, United States
4 h-index
18 publications
36.8K citations

Zhejiang University
Hangzhou, China
3 h-index
19 publications
3.5K citations

Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
313 citations
University of California System
Oakland, United States
2 h-index
7 publications
2.5K citations
Institute of Computing Technology
Beijing, China
2 h-index
4 publications
167 citations

City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
7 publications
469 citations
1–8 of 68
Repository · 9 publications · 245 citations
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TOG · 5 publications · 5.5K citations
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2 publications · 48 citations
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TPAMI · 1 publications · 25 citations
1
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Conference · 1 publications · 19 citations
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