Published in Automotive Innovation, 2025
A systematic review on certified robustness
Recommended citation: Yin, Huilin, Ziming Zhao, Jun Yan, and Daniel Watzenig. "Certified Robustness in Automated Driving Perception: A Review: H. Yin et al." Automotive Innovation (2025): 1-21.
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Published in IEEE Transactions on Information Forensics and Security, 2025
This paper addresses the significant issue in IB by incorporating causal inference into the IB-based defense framework
Recommended citation: Yan, Jun, Huan Hua, Weiquan Huang, Xi Fang, Wancheng Ge, Jiancheng Yang, and Yongwei Wang. "Exploring Causal Information Bottleneck for Adversarial Defense." IEEE Transactions on Information Forensics and Security (2025).
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Published in Information Fusion, 2025
An agile badminton robot.
Recommended citation: Shi, Zhiwei, Xingyu Zhang, Chengxi Zhu, Haochen Wang, Jun Yan, Fan Yang, and Dong Xuan. "MV-BMR: A Real-time Motion and Vision Sensing Integration based Agile Badminton Robot." Information Fusion (2025): 103337.
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Published in IEEE Signal Processing Letters, 2025
Image classifiers often degrade in performance when test images differ significantly from the training distribution due to real-world image corruptions. Frequency-based augmentations can be used to address this issue, but existing methods excel against corruptions caused by noise and blur while struggling with those caused by contrast and fog. To tackle these challenges, we propose a novel image augmentation method grounded in a new perspective of relative spectral differences.
Recommended citation: Zhang, Zhuang, Lijun Zhang, Dejian Meng, Wei Tian, and Jun Yan. "Spectral Scaling-Based Augmentation for Corruption-Robust Image Classification." IEEE Signal Processing Letters (2025).
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Published in IEEE Transactions on Artificial Intelligence, 2024
Geodesic Adversarial Training.
Recommended citation: Yan, Jun, Huilin Yin, Ziming Zhao, Wancheng Ge, and Jingfeng Zhang. "Enhance adversarial robustness via geodesic distance." IEEE Transactions on Artificial Intelligence 5, no. 8 (2024): 4202-4216.
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Published in ICRA, 2026
A novel work on the decision-based attacks aimed at the trajectory prediction system
Recommended citation: Li, Jiaxiang, Jun Yan, Daniel Watzenig, and Huilin Yin. "DTP-Attack: A decision-based black-box adversarial attack on trajectory prediction." In ICRA. 2026.
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Published in AISTATS, 2026
A spotlight paper on adversarial purification published in top-tier conference.
Recommended citation: Zhihao Dou, Zhiqiang Gao, Dongfei Cui, Weida Wang, Qinjian Zhao, Dinggen Zhang, Jun Yan, Zeke Xie, Shufei Zhang. "AMRM-Pure: Semantic-Preserving Adversarial Purification." In AISTATS. 2026.
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Published in ACM MM, 2024
An oral and wonderful paper for safe autonomous driving.
Recommended citation: Mo, Yujian, Yan Wu, Junqiao Zhao, Zhenjie Hou, Weiquan Huang, Yinghao Hu, Jijun Wang, and Jun Yan. "Sparse Query Dense: Enhancing 3D Object Detection with Pseudo points." In Proceedings of the 32nd ACM International Conference on Multimedia, pp. 409-418. 2024.
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Published in IEEE IAVVC, 2024
Best paper of IEEE IAVVC. An early work on adversarial robustness of foundation models
Recommended citation: Yan, Jun, Pengyu Wang, Danni Wang, Weiquan Huang, Daniel Watzenig, and Huilin Yin. "Segment-anything models achieve zero-shot robustness in autonomous driving." In 2024 IEEE International Automated Vehicle Validation Conference (IAVVC), pp. 1-8. IEEE, 2024.
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Published in CVPR, 2024
Multimodal Learning for AIGC Quality Assesment
Recommended citation: Fang, Xi, Weigang Wang, Xiaoxin Lv, and Jun Yan. "Pcqa: A strong baseline for aigc quality assessment based on prompt condition." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 6167-6176. 2024.
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