Learning Epipolar-Spatial Relationship for Light Field Image Super-Resolution
Author:
Affiliation:
1. Chungbuk National University,School of Information and Communication Engineering,Cheongju,Korea
Funder
National Research Foundation of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10208270/10208119/10208344.pdf?arnumber=10208344
Reference38 articles.
1. Light Field Spatial Super-Resolution Using Deep Efficient Spatial-Angular Separable Convolution
2. Accurate Image Super-Resolution Using Very Deep Convolutional Networks
3. Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization
4. Adam: A method for stochastic optimization;kingma,2014
5. Spatial-angular interaction for light field image super-resolution;wang;Computer Vision–ECCV 2020 16th European Conference Glasgow UK August 23–28 2020 Proceedings Part XXIII 16,2020
Cited by 1 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. NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06
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