Yao Zhu

According to our database, Yao Zhu authored at least 16 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Enhancing Few-Shot CLIP With Semantic-Aware Fine-Tuning.

Yao Zhu, Yuefeng Chen, Xiaofeng Mao, Xiu Yan, Yue Wang, Wang Lu, Jindong Wang, Xiangyang Ji

IEEE Trans. Neural Networks Learn. Syst., July, 2025

Towards Boosting Out-of-Distribution Detection from a Spatial Feature Importance Perspective.

Yao Zhu, Xiu Yan, Chuanlong Xie

Int. J. Comput. Vis., July, 2025

Enhancing the Robustness of Vision-Language Foundation Models by Alignment Perturbation.

Cong Zhang, Shuhui Wang, Xiaodan Li, Yao Zhu, Honggang Qi, Qingming Huang

IEEE Trans. Inf. Forensics Secur., 2025

2024

Rethinking Out-of-Distribution Detection From a Human-Centric Perspective.

Yao Zhu, Yuefeng Chen, Xiaodan Li, Rong Zhang, Hui Xue, Xiang Tian, Rongxin Jiang, Bolun Zheng, Yaowu Chen

Int. J. Comput. Vis., October, 2024

2023

Information-Containing Adversarial Perturbation for Combating Facial Manipulation Systems.

Yao Zhu, Yuefeng Chen, Xiaodan Li, Rong Zhang, Xiang Tian, Bolun Zheng, Yaowu Chen

IEEE Trans. Inf. Forensics Secur., 2023

Enhancing Few-shot CLIP with Semantic-Aware Fine-Tuning.

Yao Zhu, Yuefeng Chen, Wei Wang, Xiaofeng Mao, Xiu Yan, Yue Wang, Zhigang Li, Wang Lu, Jindong Wang, Xiangyang Ji

CoRR, 2023

Inequality phenomenon in l_∞-adversarial training, and its unrealized threats.

Ranjie Duan, Yuefeng Chen, Yao Zhu, Xiaojun Jia, Rong Zhang, Hui Xue

Proceedings of the Eleventh International Conference on Learning Representations, 2023

COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts.

Xiaofeng Mao, Yuefeng Chen, Yao Zhu, Da Chen, Hang Su, Rong Zhang, Hui Xue

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Transaudio: Towards the Transferable Adversarial Audio Attack Via Learning Contextualized Perturbations.

Gege Qi, Yuefeng Chen, Yao Zhu, Binyuan Hui, Xiaodan Li, Xiaofeng Mao, Rong Zhang, Hui Xue

Proceedings of the IEEE International Conference on Acoustics, 2023

ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing.

Xiaodan Li, Yuefeng Chen, Yao Zhu, Shuhui Wang, Rong Zhang, Hui Xue

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Toward Understanding and Boosting Adversarial Transferability From a Distribution Perspective.

Yao Zhu, Yuefeng Chen, Xiaodan Li, Kejiang Chen, Yuan He, Xiang Tian, Bolun Zheng, Yaowu Chen, Qingming Huang

IEEE Trans. Image Process., 2022

Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective.

Yao Zhu, Yuefeng Chen, Xiaodan Li, Kejiang Chen, Yuan He, Xiang Tian, Bolun Zheng, Yaowu Chen, Qingming Huang

CoRR, 2022

Boosting Out-of-distribution Detection with Typical Features.

Yao Zhu, Yuefeng Chen, Chuanlong Xie, Xiaodan Li, Rong Zhang, Hui Xue, Xiang Tian, Bolun Zheng, Yaowu Chen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Enhance the Visual Representation via Discrete Adversarial Training.

Xiaofeng Mao, Yuefeng Chen, Ranjie Duan, Yao Zhu, Gege Qi, Shaokai Ye, Xiaodan Li, Rong Zhang, Hui Xue

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Towards Understanding the Generative Capability of Adversarially Robust Classifiers.

Yao Zhu, Jiacheng Ma, Jiacheng Sun, Zewei Chen, Rongxin Jiang, Zhenguo Li

CoRR, 2021

Towards Understanding the Generative Capability of Adversarially Robust Classifiers.

Yao Zhu, Jiacheng Ma, Jiacheng Sun, Zewei Chen, Rongxin Jiang, Yaowu Chen, Zhenguo Li

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021