activity
20192021
most citedQuery2Label: A Simple Transformer Way to Multi-Label Classification

121 citations · 153 across the 8 of their papers we have counts for

collaborators

12 papers

cs.CV20216 cited

Unrestricted Adversarial Attacks on ImageNet Competition

Yuefeng Chen, Xiaofeng Mao, Yuan He +34

Many works have investigated the adversarial attacks or defenses under the settings where a bounded and imperceptible perturbation can be added to the input. However in the real-wo…

cs.CV20211 cited

Adversarial Attacks on ML Defense Models Competition

Yinpeng Dong, Qi-An Fu, Xiao Yang +25

Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…

cs.LG20211 cited

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness

Xiao Yang, Yinpeng Dong, Wenzhao Xiang +3

The vulnerability of deep neural networks to adversarial examples has motivated an increasing number of defense strategies for promoting model robustness. However, the progress is…

cs.CV2021

Adversarial Semantic Contour for Object Detection

Yichi Zhang, Zijian Zhu, Xiao Yang +1

Modern object detectors are vulnerable to adversarial examples, which brings potential risks to numerous applications, e.g., self-driving car. Among attacks regularized by

cs.CV2021121 cited

Query2Label: A Simple Transformer Way to Multi-Label Classification

Shilong Liu, Lei Zhang, Xiao Yang +2

This paper presents a simple and effective approach to solving the multi-label classification problem. The proposed approach leverages Transformer decoders to query the existence o…

cs.LG2021

Accumulative Poisoning Attacks on Real-time Data

Tianyu Pang, Xiao Yang, Yinpeng Dong +2

Collecting training data from untrusted sources exposes machine learning services to poisoning adversaries, who maliciously manipulate training data to degrade the model accuracy.…