25 citations · 32 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Zihao Xiao, Xianfeng Gao, Chilin Fu +5
Face recognition is greatly improved by deep convolutional neural networks (CNNs). Recently, these face recognition models have been used for identity authentication in security se…
Data-Free Adversarial Perturbations for Practical Black-Box Attack
ZhaoXin Huan, Yulong Wang, Xiaolu Zhang +3
Neural networks are vulnerable to adversarial examples, which are malicious inputs crafted to fool pre-trained models. Adversarial examples often exhibit black-box attacking transf…
Pruning from Scratch
Yulong Wang, Xiaolu Zhang, Lingxi Xie +4
Network pruning is an important research field aiming at reducing computational costs of neural networks. Conventional approaches follow a fixed paradigm which first trains a large…