Dongxian Wu

According to our database, Dongxian Wu authored at least 14 papers between 2020 and 2023.

Collaborative distances:

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

2023

Not All Samples Are Born Equal: Towards Effective Clean-Label Backdoor Attacks.

Yinghua Gao, Yiming Li, Linghui Zhu, Dongxian Wu, Yong Jiang, Shu-Tao Xia

Pattern Recognit., July, 2023

Towards Robust Model Watermark via Reducing Parametric Vulnerability.

Guanhao Gan, Yiming Li, Dongxian Wu, Shu-Tao Xia

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

Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning.

Kuofeng Gao, Jiawang Bai, Bin Chen, Dongxian Wu, Shu-Tao Xia

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

On the Effectiveness of Adversarial Training against Backdoor Attacks.

Yinghua Gao, Dongxian Wu, Jingfeng Zhang, Guanhao Gan, Shu-Tao Xia, Gang Niu, Masashi Sugiyama

CoRR, 2022

When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture.

Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang

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

2021

Clean-label Backdoor Attack against Deep Hashing based Retrieval.

Kuofeng Gao, Jiawang Bai, Bin Chen, Dongxian Wu, Shu-Tao Xia

CoRR, 2021

Adversarial Neuron Pruning Purifies Backdoored Deep Models.

Dongxian Wu, Yisen Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Revisiting Loss Landscape for Adversarial Robustness.

Dongxian Wu, Yisen Wang, Shutao Xia

CoRR, 2020

Adversarial Weight Perturbation Helps Robust Generalization.

Dongxian Wu, Shu-Tao Xia, Yisen Wang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DIPDefend: Deep Image Prior Driven Defense against Adversarial Examples.

Tao Dai, Yan Feng, Dongxian Wu, Bin Chen, Jian Lu, Yong Jiang, Shu-Tao Xia

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Temporal Calibrated Regularization for Robust Noisy Label Learning.

Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shu-Tao Xia

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Matrix Smoothing: A Regularization For Dnn With Transition Matrix Under Noisy Labels.

Xianbin Lv, Dongxian Wu, Shu-Tao Xia

Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets.

Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma

Proceedings of the 8th International Conference on Learning Representations, 2020

Targeted Attack for Deep Hashing Based Retrieval.

Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang

Proceedings of the Computer Vision - ECCV 2020, 2020