Uncertainty-Driven Dynamic Degradation Perceiving and Background Modeling for Efficient Single Image Desnowing-Reference-Cited by-同舟云学术

Uncertainty-Driven Dynamic Degradation Perceiving and Background Modeling for Efficient Single Image Desnowing

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
language:
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Author:

Chen Sixiang¹^ORCID,Ye Tian¹^ORCID,Xue Chenghao²^ORCID,Chen Haoyu¹^ORCID,Liu Yun³^ORCID,Chen Erkang⁴^ORCID,Zhu Lei⁵^ORCID

Affiliation:

1. The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

2. Jimei University, Xiamen, China

3. Southwest University, Chongqing, China

4. Jimei University, Xiamne, China

5. The Hong Kong University of Science and Technology (Guangzhou) & The Hong Kong University of Science and Technology, Guangzhou & New Territories, China

Funder

the Guangzhou Municipal Science and Technology Project

HKUST(GZ) Industrial Informatics and Intelligence Institute

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612003

Reference83 articles.

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2. Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks

3. Data Uncertainty Learning in Face Recognition

4. Video anomaly detection with spatio-temporal dissociation

5. Masked Image Training for Generalizable Deep Image Denoising

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