Visually Source-Free Domain Adaptation via Adversarial Style Matching-Reference-Cited by-同舟云学术

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Visually Source-Free Domain Adaptation via Adversarial Style Matching

Published:2024 Issue: Volume:33 Page:1032-1044
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Jing Mengmeng¹^ORCID,Li Jingjing²^ORCID,Lu Ke²^ORCID,Zhu Lei³^ORCID,Shen Heng Tao²^ORCID

Affiliation:

1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China

3. School of Electronic and Information Engineering, Tongji University, Shanghai, China

Funder

National Natural Science Foundation of China

Sichuan Science and Technology Program

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

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/83/10346232/10410236.pdf?arnumber=10410236

Reference83 articles.

1. A Survey on Transfer Learning

2. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

3. Conditional adversarial domain adaptation;Long

4. ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

5. AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection

Cited by 1 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. Dual Classifier Adaptation: Source-Free UDA via Adaptive Pseudo-Labels Learning;Neural Processing Letters;2024-05-04

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