Fooling the Image Dehazing Models by First Order Gradient-Reference-Cited by-同舟云学术

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Fooling the Image Dehazing Models by First Order Gradient

Published:2024-07 Issue:7 Volume:34 Page:6265-6278
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Gui Jie¹^ORCID,Cong Xiaofeng¹^ORCID,Peng Chengwei²^ORCID,Tang Yuan Yan³^ORCID,Kwok James Tin-Yau⁴^ORCID

Affiliation:

1. School of Cyber Science and Engineering, Southeast University, Nanjing, China

2. Tecent Company, Shenzhen, China

3. Department of Computer and Information Science, University of Macau, Macau, China

4. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

Funder

National Key Research and Development Program of China

National Science Foundation of China

Fundamental Research Funds for the Central Universities

Chinese Association for Artificial Intelligence (CAAI)-Huawei MindSpore Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/76/10582818/10414993.pdf?arnumber=10414993

Reference58 articles.

1. Towards Multi-domain Single Image Dehazing via Test-time Training

2. Self-augmented Unpaired Image Dehazing via Density and Depth Decomposition

3. WSAMF-Net: Wavelet Spatial Attention-Based MultiStream Feedback Network for Single Image Dehazing

4. TMS-GAN: A Twofold Multi-scale Generative Adversarial Network for Single Image Dehazing

5. Hierarchical Feature Fusion With Mixed Convolution Attention for Single Image Dehazing

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