Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation

Author:

Chao Wentao1ORCID,Wang Xuechun1ORCID,Wang Yingqian2ORCID,Wang Guanghui3ORCID,Duan Fuqing1ORCID

Affiliation:

1. School of Artificial Intelligence, Beijing Normal University, Beijing, China

2. College of Electronic Science and Technology, National University of Defense Technology, Changsha, China

3. Department of Computer Science, Toronto Metropolitan University, Toronto, ON, Canada

Funder

National Key Research and Development

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Mathematics,Computer Science Applications,Signal Processing

Cited by 6 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. Occlusion Handling in Depth Estimation of a Scene from a Given Light Field Using a Geodesic Distance and the Principle of Symmetry of the View;Journal of Communications Technology and Electronics;2024-09-11

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. LFDA: A Framework for Light Field Depth Estimation With Depth Attention;IEEE Access;2024

4. ContextNet: Learning Context Information for Texture-Less Light Field Depth Estimation;Pattern Recognition and Computer Vision;2023-12-26

5. D-IF: Uncertainty-aware Human Digitization via Implicit Distribution Field;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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