Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion-Reference-Cited by-同舟云学术

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Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion

Published:2022 Issue: Volume:31 Page:3525-3540
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Liao Liang¹^ORCID,Chen Wenyi²,Xiao Jing²^ORCID,Wang Zheng²^ORCID,Lin Chia-Wen³^ORCID,Satoh Shin'ichi¹^ORCID

Affiliation:

1. Digital Content and Media Sciences Research Division, National Institute of Informatics, Tokyo, Japan

2. School of Computer Science, Wuhan University, Wuhan, China

3. Department of Electrical Engineering, Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan

Funder

National Natural Science Foundation of China

National Key Research and Development Project

Ministry of Science and Technology, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09771097.pdf?arnumber=9771097

Reference58 articles.

1. Automatic Adaptation of Object Detectors to New Domains Using Self-Training

2. Generative attention adversarial classification network for unsupervised domain adaptation

3. Context-Reinforced Semantic Segmentation

4. Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation

5. Squeeze-and-Attention Networks for Semantic Segmentation

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