Neural Radiance Fields
Neural Radiance Fields is a computational framework that represents a 3D scene as a continuous volumetric radiance field, parameterized by a neural network to model the color and density of points in space, enabling synthesis of photorealistic novel views from sparse 2D image inputs.
524
Publications
49.5K
Citations
1.5K
Authors
271
Institutions
Publications per year
2017–2026
523
524
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik et al. · Communications of the ACM · 2021 · 5.8K citations · Full text
pixelNeRF: Neural Radiance Fields from One or Few Images
Alex Yu, Vickie Ye, Matthew Tancik et al. · 2021 · 1.4K citations
1–5 of 524
1.5K
28
h-index
19
h-index
16
h-index
15
h-index
14
h-index
1–5 of 1.5K
271
Google (United States)
Mountain View, United States
39 h-index
188 publications
47K citations

Zhejiang University
Hangzhou, China
23 h-index
99 publications
7.8K citations
Tsinghua University
Beijing, China
19 h-index
66 publications
4.7K citations
Tencent (China)
Shenzhen, China
19 h-index
62 publications
4.1K citations
Max Planck Institute for Informatics
Saarbrücken, Germany
14 h-index
46 publications
4.6K citations
Carnegie Mellon University
Pittsburgh, United States
14 h-index
31 publications
4.7K citations
University of California, Berkeley
Berkeley, United States
13 h-index
59 publications
52.9K citations
Meta (Israel)
Tel Aviv, Israel
13 h-index
43 publications
5.6K citations
1–8 of 271
Conference · 48 publications · 12.6K citations
43
h-index
Repository · 93 publications · 4.8K citations
35
h-index
TOG · 22 publications · 2.4K citations
20
h-index
Conference · 20 publications · 4.3K citations
19
h-index
TVCG · 8 publications · 785 citations
10
h-index
1–5