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Cluster and Scatter: A Multi-grained Active Semi-supervised Learning Framework for Scalable Person Re-identification

  • Published:2021-10-17 Issue: Volume: Page:
  • ISSN:
  • Container-title:Proceedings of the 29th ACM International Conference on Multimedia
  • language:
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Author:

Hu Bingyu1,Zha Zheng-Jun1,Liu Jiawei1,Zhu Xierong1,Xie Hongtao1

Affiliation:

1. University of Science and Technology of China, Hefei, China

Funder

China Postdoctoral Science Foundation Funded Project

National Natural Science Foundation of China (NSFC)

the University Synergy Innovation Program of Anhui Province

National Key R&D Program of China

Publisher

ACM

Cited by 6 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. Improving the performance of semi-supervised person Re-identification by selecting reliable unlabeled samples;Engineering Applications of Artificial Intelligence;2024-07

2. Multi- View Teacher with Curriculum Data Fusion for Robust Unsupervised Domain Adaptation;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

3. AffectFAL: Federated Active Affective Computing with Non-IID Data;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

4. Semi-supervised and un-supervised clustering: A review and experimental evaluation;Information Systems;2023-03

5. Highly Efficient Active Learning With Tracklet-Aware Co-Cooperative Annotators for Person Re-Identification;IEEE Transactions on Neural Networks and Learning Systems;2023
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