88 citations · 359 across the 23 of their papers we have counts for
31 papers
Artificial Intelligence Security Competition (AISC)
Yinpeng Dong, Peng Chen, Senyou Deng +49
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems. To accelerate the research on AI security, the Artifi…
Improving transferability of 3D adversarial attacks with scale and shear transformations
Jinali Zhang, Yinpeng Dong, Jun Zhu +3
Previous work has shown that 3D point cloud classifiers can be vulnerable to adversarial examples. However, most of the existing methods are aimed at white-box attacks, where the p…
Isometric 3D Adversarial Examples in the Physical World
Yibo Miao, Yinpeng Dong, Jun Zhu +1
3D deep learning models are shown to be as vulnerable to adversarial examples as 2D models. However, existing attack methods are still far from stealthy and suffer from severe perf…
Pre-trained Adversarial Perturbations
Yuanhao Ban, Yinpeng Dong
Self-supervised pre-training has drawn increasing attention in recent years due to its superior performance on numerous downstream tasks after fine-tuning. However, it is well-know…
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
Yinpeng Dong, Shouwei Ruan, Hang Su +3
Recent studies have demonstrated that visual recognition models lack robustness to distribution shift. However, current work mainly considers model robustness to 2D image transform…
BadDet: Backdoor Attacks on Object Detection
Shih-Han Chan, Yinpeng Dong, Jun Zhu +2
Deep learning models have been deployed in numerous real-world applications such as autonomous driving and surveillance. However, these models are vulnerable in adversarial environ…