Deep Light Field Spatial Super-Resolution Using Heterogeneous Imaging
Author:
Affiliation:
1. Faculty of Information Science and Engineering, Ningbo University, Ningbo, China
2. School of Electrical Engineering and ComputerScience, Gwangju Institute of Science and Technology, Gwangju, South Korea
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Signal Processing,Software
Link
http://xplorestaging.ieee.org/ielx7/2945/4359476/09798876.pdf?arnumber=9798876
Cited by 11 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. Light Field Spatial Super-Resolution via View Interaction and the Fusing of Hierarchical Features;Electronics;2024-06-17
2. Hybrid Domain Learning towards Light Field Spatial Super-Resolution using Heterogeneous Imaging;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
3. Learning zero-shot dense light field reconstruction from heterogeneous imaging;Information Fusion;2024-03
4. MAFBLiF: Multi-Scale Attention Feature Fusion-Based Blind Light Field Image Quality Assessment;IEEE Transactions on Broadcasting;2024
5. Multi-Scale Spatial-Angular Collaborative Guidance Network for Heterogeneous Light Field Spatial Super-Resolution;IEEE Transactions on Broadcasting;2024
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