An Untrained Neural Network Prior for Light Field Compression-Reference-Cited by-同舟云学术

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An Untrained Neural Network Prior for Light Field Compression

Published:2022 Issue: Volume:31 Page:6922-6936
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Jiang Xiaoran¹^ORCID,Shi Jinglei¹^ORCID,Guillemot Christine¹^ORCID

Affiliation:

1. Inria Centre de Recherche Rennes—Bretagne Atlantique, Rennes, France

Funder

European Union (EU) H2020 Research and Innovation Programme [European Research Council (ERC) Advanced Grant Computational Light Field Imaging (CLIM)]

French Agence Nationale de la Recherche (ANR) Research Agency in the Context of the Artificial Intelligence Project DeepCIM

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09934016.pdf?arnumber=9934016

Reference75 articles.

1. Context-adaptive entropy model for end-to-end optimized image compression;lee;Proc Int Conf Learn Represent (ICLR),2019

2. Training with quantization noise for extreme model compression;fan;Proc Int Conf Learn Represent (ICLR),2021

3. Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding;han;arXiv 1510 00149 [cs],2015

4. Full Resolution Image Compression with Recurrent Neural Networks

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient random-access GPU video decoding for light-field rendering;Journal of Visual Communication and Image Representation;2024-06

2. Learning Kernel-Modulated Neural Representation for Efficient Light Field Compression;IEEE Transactions on Image Processing;2024

3. MFI-Net: Multi-feature Fusion Identification Networks for Artificial Intelligence Manipulation;IEEE Transactions on Circuits and Systems for Video Technology;2023

4. Space-Time Super-Resolution for Light Field Videos;IEEE Transactions on Image Processing;2023

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