FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos-Reference-Cited by-同舟云学术

FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Lee Joo Chan¹^ORCID,Rho Daniel²^ORCID,Ko Jong Hwan¹^ORCID,Park Eunbyung¹^ORCID

Affiliation:

1. Sungkyunkwan University, Suwon, Republic of Korea

2. KT, Seoul, Republic of Korea

Funder

Institute of Information and Communication Technology Planning Evaluation (IITP)

Ministry of Trade Industry & Energy

Technology Innovation Program

Ministry of Science and ICT (MSIT) of Korea

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612444

Reference56 articles.

1. Scale-Space Flow for End-to-End Optimized Video Compression

2. Scale-Space Flow for End-to-End Optimized Video Compression

3. Yunpeng Bai Chao Dong and Cairong Wang. 2022. PS-NeRV: Patch-wise Stylized Neural Representations for Videos. arXiv preprint arXiv:2208.03742. Yunpeng Bai Chao Dong and Cairong Wang. 2022. PS-NeRV: Patch-wise Stylized Neural Representations for Videos. arXiv preprint arXiv:2208.03742.

4. Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields

5. Anpei Chen , Zexiang Xu , Andreas Geiger , Jingyi Yu , and Hao Su . 2022 b. TensoRF: Tensorial Radiance Fields. In European Conference on Computer Vision. 333--350 . Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su. 2022b. TensoRF: Tensorial Radiance Fields. In European Conference on Computer Vision. 333--350.

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