Video Snapshot Compressive Imaging via Deep Learning with Adversarial Training

Honghao Huang; Chengyang Hu; Sigang Yang; Minghua Chen; Hongwei Chen

doi:10.1364/CLEO_AT.2022.JW3B.172

Conference on Lasers and Electro-Optics
Technical Digest Series (Optica Publishing Group, 2022),
paper JW3B.172
•https://doi.org/10.1364/CLEO_AT.2022.JW3B.172

Video Snapshot Compressive Imaging via Deep Learning with Adversarial Training

Honghao Huang, Chengyang Hu, Sigang Yang, Minghua Chen, and Hongwei Chen

CLEO: Applications and Technology 2022

San Jose, California United States
15–20 May 2022
ISBN: 978-1-957171-05-0

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Joint Poster Session II-B (Virtual) (JW3B)

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H. Huang, C. Hu, S. Yang, M. Chen, and H. Chen, "Video Snapshot Compressive Imaging via Deep Learning with Adversarial Training," in Conference on Lasers and Electro-Optics, Technical Digest Series (Optica Publishing Group, 2022), paper JW3B.172.

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Abstract

We present deep learning with adversarial training for video compressive imaging, which can recover 50 frames from a snapshot with boosted visual quality compared to typical iterative algorithm and neural network with simple loss function.

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