publications

2024

1. ECCV

   PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition

   Xiao Li, Yining Liu, Na Dong, Sitian Qin, and Xiaolin Hu

   European Conference on Computer Vision (ECCV), 2024

   Bib arXiv Code

   @article{lipartimagenetpp,
     title = {PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition},
     author = {Li, Xiao and Liu, Yining and Dong, Na and Qin, Sitian and Hu, Xiaolin},
     journal = {European Conference on Computer Vision (ECCV)},
     year = {2024},
     publisher = {Springer}
   }

   

2. arXiv

   ADBM: Adversarial diffusion bridge model for reliable adversarial purification

   Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yining Liu, Yingzhe He, Jie Shi, and Xiaolin Hu

   arXiv preprint arXiv:2408.00315, 2024

   Bib arXiv

   @article{li2024adbm,
     title = {ADBM: Adversarial diffusion bridge model for reliable adversarial purification},
     author = {Li, Xiao and Sun, Wenxuan and Chen, Huanran and Li, Qiongxiu and Liu, Yining and He, Yingzhe and Shi, Jie and Hu, Xiaolin},
     journal = {arXiv preprint arXiv:2408.00315},
     year = {2024}
   }

   

3. CVPR

   Language-Driven Anchors for Zero-Shot Adversarial Robustness

   Xiao Li, Wei Zhang, Yining Liu, Zhanhao Hu, Bo Zhang, and Xiaolin Hu

   In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

   Bib arXiv Code

   @inproceedings{li2023languagedriven,
     author = {Li, Xiao and Zhang, Wei and Liu, Yining and Hu, Zhanhao and Zhang, Bo and Hu, Xiaolin},
     title = {Language-Driven Anchors for Zero-Shot Adversarial Robustness},
     booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages = {24686--24695},
     year = {2024}
   }

   

4. TIFS

   On the Privacy Effect of Data Enhancement via the Lens of Memorization

   Xiao Li, Qiongxiu Li, Zhanhao Hu, and Xiaolin Hu

   IEEE Transactions on Information Forensics and Security (TIFS), 2024

   Bib arXiv Code

   @article{li2024privacy,
     title = {On the Privacy Effect of Data Enhancement via the Lens of Memorization},
     author = {Li, Xiao and Li, Qiongxiu and Hu, Zhanhao and Hu, Xiaolin},
     journal = {{IEEE} Transactions on Information Forensics and Security (TIFS)},
     year = {2024}
   }

   

5. Neuroc..

   Hiding from thermal imaging pedestrian detectors in the physical world

   Xiaopei Zhu, Xiao Li, Jianmin Li, Zheyao Wang, and Xiaolin Hu

   Neurocomputing, 2024

   Bib

   @article{zhu2024hiding,
     link = {https://www.sciencedirect.com/science/article/abs/pii/S0925231223010469},
     title = {Hiding from thermal imaging pedestrian detectors in the physical world},
     author = {Zhu, Xiaopei and Li, Xiao and Li, Jianmin and Wang, Zheyao and Hu, Xiaolin},
     journal = {Neurocomputing},
     volume = {564},
     pages = {126923},
     year = {2024},
     publisher = {Elsevier}
   }

   

2023

1. arXiv

   On the Importance of Backbone to the Adversarial Robustness of Object Detectors

   Xiao Li, Hang Chen, and Xiaolin Hu

   arXiv preprint arXiv:2305.17438, 2023

   Bib arXiv

   @article{li2023importance,
     title = {On the Importance of Backbone to the Adversarial Robustness of Object Detectors},
     author = {Li, Xiao and Chen, Hang and Hu, Xiaolin},
     journal = {arXiv preprint arXiv:2305.17438},
     year = {2023}
   }

   

2. TPAMI

   Recognizing Object by Components With Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks

   Xiao Li, Ziqi Wang, Bo Zhang, Fuchun Sun, and Xiaolin Hu

   IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023

   Bib arXiv Code

   @article{rock,
     author = {Li, Xiao and Wang, Ziqi and Zhang, Bo and Sun, Fuchun and Hu, Xiaolin},
     title = {Recognizing Object by Components With Human Prior Knowledge Enhances
                       Adversarial Robustness of Deep Neural Networks},
     journal = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
     volume = {45},
     number = {7},
     pages = {8861--8873},
     year = {2023}
   }

   

2022

1. IJCV

   Improving Image Segmentation with Boundary Patch Refinement

   Xiaolin Hu, Chufeng Tang, Hang Chen, Xiao Li, Jianmin Li, and Zhaoxiang Zhang

   International Journal of Computer Vision (IJCV), 2022

   Bib

   @article{hu2022improving,
     link = {https://link.springer.com/article/10.1007/s11263-022-01662-0},
     title = {Improving Image Segmentation with Boundary Patch Refinement},
     author = {Hu, Xiaolin and Tang, Chufeng and Chen, Hang and Li, Xiao and Li, Jianmin and Zhang, Zhaoxiang},
     journal = {International Journal of Computer Vision (IJCV)},
     volume = {130},
     number = {11},
     pages = {2571--2589},
     year = {2022},
     publisher = {Springer}
   }

   

2021

1. CVPR

   Look closer to segment better: Boundary patch refinement for instance segmentation

   Chufeng Tang, Hang Chen, Xiao Li, Jianmin Li, Zhaoxiang Zhang, and Xiaolin Hu

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

   Bib Code

   @inproceedings{tang2021look,
     title = {Look closer to segment better: Boundary patch refinement for instance segmentation},
     author = {Tang, Chufeng and Chen, Hang and Li, Xiao and Li, Jianmin and Zhang, Zhaoxiang and Hu, Xiaolin},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages = {13926--13935},
     year = {2021}
   }

   

2. AAAI

   Fooling thermal infrared pedestrian detectors in real world using small bulbs

   Xiaopei Zhu, Xiao Li, Jianmin Li, Zheyao Wang, and Xiaolin Hu

   In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021

   Bib

   @inproceedings{zhu2021fooling,
     link = {https://ojs.aaai.org/index.php/AAAI/article/view/16477},
     title = {Fooling thermal infrared pedestrian detectors in real world using small bulbs},
     author = {Zhu, Xiaopei and Li, Xiao and Li, Jianmin and Wang, Zheyao and Hu, Xiaolin},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
     volume = {35},
     number = {4},
     pages = {3616--3624},
     year = {2021}
   }