Neural Fields in Visual Computing and Beyond
Author:
Affiliation:
1. Brown University
2. Unity Technologies
3. University of Toronto
4. NVIDIA
5. Meta Reality Labs Research
6. Google
7. Technical University of Munich
8. Massachusetts Institute of Technology
9. Equal advising
Funder
National Science Foundation
Publisher
Wiley
Subject
Computer Graphics and Computer-Aided Design
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.14505
Reference418 articles.
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2. AnokhinI. DemochkinK. KhakhulinT. SterkinG. LempitskyV. KorzhenkovD.: Image generators with conditionally-independent pixel synthesis. InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2021). URL:http://arxiv.org/abs/2011.13775v1. 16 17
3. AtzmonM. HaimN. YarivL. IsraelovO. MaronH. LipmanY.: Controlling neural level sets. InAdvances in Neural Information Processing Systems (NeurIPS)(2019) Curran Associates Inc. URL:http://arxiv.org/abs/1905.11911v2. 13
4. AttalB. HuangJ.-B. ZollhoeferM. KopfJ. KimC.: Learning neural light fields with ray-space embedding networks.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(2022). 14
5. AtzmonM. LipmanY.: Sal: Sign agnostic learning of shapes from raw data. InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2020). URL:http://arxiv.org/abs/1911.10414v2. 13
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