401 citations · 916 across the 20 of their papers we have counts for
5 papers · 1 filter
Learning Transferable Adversarial Examples via Ghost Networks
Yingwei Li, Song Bai, Yuyin Zhou +3
Recent development of adversarial attacks has proven that ensemble-based methods outperform traditional, non-ensemble ones in black-box attack. However, as it is computationally pr…
Robust Face Detection via Learning Small Faces on Hard Images
Zhishuai Zhang, Wei Shen, Siyuan Qiao +3
Recent anchor-based deep face detectors have achieved promising performance, but they are still struggling to detect hard faces, such as small, blurred and partially occluded faces…
Adversarial Attacks and Defences Competition
Alexey Kurakin, Ian Goodfellow, Samy Bengio +20
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop…
Deep Co-Training for Semi-Supervised Image Recognition
Siyuan Qiao, Wei Shen, Zhishuai Zhang +2
In this paper, we study the problem of semi-supervised image recognition, which is to learn classifiers using both labeled and unlabeled images. We present Deep Co-Training, a deep…
Improving Transferability of Adversarial Examples with Input Diversity
Cihang Xie, Zhishuai Zhang, Yuyin Zhou +4
Though CNNs have achieved the state-of-the-art performance on various vision tasks, they are vulnerable to adversarial examples --- crafted by adding human-imperceptible perturbati…