publications

2026

1. ICML

   

   Is Spurious Correlation Removal Always Learnable?

   Yibo Zhou, Bo Li, Hai-Miao Hu, Hanzi Wang, Xiaokang Zhang, and Ruifan Zhang

   In International Conference on Machine Learning, 2026

   Accepted at ICML 2026

   arXiv Bib

   @inproceedings{zhou2026spurious,
     author = {Zhou, Yibo and Li, Bo and Hu, Hai-Miao and Wang, Hanzi and Zhang, Xiaokang and Zhang, Ruifan},
     title = {Is Spurious Correlation Removal Always Learnable?},
     booktitle = {International Conference on Machine Learning},
     year = {2026},
     note = {Accepted at ICML 2026},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG},
     url = {https://arxiv.org/abs/2606.12930},
   }

2025

1. TPAMI

   

   Heterogeneous Feature Re-Sampling for Balanced Pedestrian Attribute Recognition

   Yibo Zhou, Bo Li, Hai-Miao Hu, Xiaokang Zhang, Dongping Zhang, and Hanzi Wang

   IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

   DOI Bib

   @article{zhou2025heterogeneous,
     author = {Zhou, Yibo and Li, Bo and Hu, Hai-Miao and Zhang, Xiaokang and Zhang, Dongping and Wang, Hanzi},
     title = {Heterogeneous Feature Re-Sampling for Balanced Pedestrian Attribute Recognition},
     journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
     volume = {47},
     number = {4},
     pages = {2706--2722},
     year = {2025},
     doi = {10.1109/TPAMI.2025.3526930},
     url = {https://doi.org/10.1109/TPAMI.2025.3526930},
   }

2. IJCV

   

   A Solution to Co-occurrence Bias in Pedestrian Attribute Recognition: Theory, Algorithms, and Improvements

   Yibo Zhou, Hai-Miao Hu, Jinzuo Yu, Haotian Wu, Shiliang Pu, and Hanzi Wang

   International Journal of Computer Vision, 2025

   DOI Bib

   @article{zhou2025cooccurrence,
     author = {Zhou, Yibo and Hu, Hai-Miao and Yu, Jinzuo and Wu, Haotian and Pu, Shiliang and Wang, Hanzi},
     title = {A Solution to Co-occurrence Bias in Pedestrian Attribute Recognition: Theory, Algorithms, and Improvements},
     journal = {International Journal of Computer Vision},
     volume = {133},
     number = {7},
     pages = {4712--4726},
     year = {2025},
     doi = {10.1007/s11263-025-02405-7},
     url = {https://doi.org/10.1007/s11263-025-02405-7},
   }

2024

1. ICML

   

   Pedestrian Attribute Recognition as Label-Balanced Multi-Label Learning

   Yibo Zhou, Hai-Miao Hu, Yirong Xiang, Xiaokang Zhang, and Haotian Wu

   In Proceedings of the 41st International Conference on Machine Learning, Jul 2024

   Bib PDF

   @inproceedings{pmlr-v235-zhou24j,
     title = {Pedestrian Attribute Recognition as Label-Balanced Multi-Label Learning},
     author = {Zhou, Yibo and Hu, Hai-Miao and Xiang, Yirong and Zhang, Xiaokang and Wu, Haotian},
     booktitle = {Proceedings of the 41st International Conference on Machine Learning},
     pages = {61964--61978},
     year = {2024},
     editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
     volume = {235},
     series = {Proceedings of Machine Learning Research},
     month = jul,
     publisher = {PMLR},
     url = {https://proceedings.mlr.press/v235/zhou24j.html},
   }

2023

1. IJCAI

   

   A Solution to Co-occurrence Bias: Attributes Disentanglement via Mutual Information Minimization for Pedestrian Attribute Recognition

   Yibo Zhou, Hai-Miao Hu, Jinzuo Yu, Zhenbo Xu, Weiqing Lu, and Yuran Cao

   In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, Aug 2023

   Main Track

   DOI Bib

   @inproceedings{ijcai2023p203,
     title = {A Solution to Co-occurrence Bias: Attributes Disentanglement via Mutual Information Minimization for Pedestrian Attribute Recognition},
     author = {Zhou, Yibo and Hu, Hai-Miao and Yu, Jinzuo and Xu, Zhenbo and Lu, Weiqing and Cao, Yuran},
     booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence},
     publisher = {International Joint Conferences on Artificial Intelligence Organization},
     editor = {Elkind, Edith},
     pages = {1831--1839},
     year = {2023},
     month = aug,
     note = {Main Track},
     doi = {10.24963/ijcai.2023/203},
     url = {https://doi.org/10.24963/ijcai.2023/203},
   }

2022

1. CVPR

   

   Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection

   Yibo Zhou

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

   DOI Bib

   @inproceedings{zhou2022rethinking,
     author = {Zhou, Yibo},
     title = {Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
     pages = {7379--7387},
     year = {2022},
     doi = {10.1109/CVPR52688.2022.00723},
     url = {https://doi.org/10.1109/CVPR52688.2022.00723},
   }