Universal Semi-supervised Model Adaptation via Collaborative Consistency Training-Reference-Cited by-同舟云学术

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Universal Semi-supervised Model Adaptation via Collaborative Consistency Training

Published:2024-01-03 Issue: Volume:34 Page:861-871
ISSN:
Container-title:2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Yan Zizheng¹,Wu Yushuang¹,Qin Yipeng²,Han Xiaoguang¹,Cui Shuguang¹,Li Guanbin³

Affiliation:

1. FNii, CUHKSZ

2. Cardiff University

3. Sun Yat-sen University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10483279/10483282/10483992.pdf?arnumber=10483992

Reference61 articles.

1. A closer look at memorization in deep networks;Arpit

2. Neural machine translation by jointly learning to align and translate;Bahdanau,2014

3. Mixmatch: A holistic approach to semi-supervised learning;Berthelot,2019

4. Adamatch: A unified approach to semi-supervised learning and domain adaptation;Berthelot

5. Partial Adversarial Domain Adaptation

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