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20092023
most citedTriple Generative Adversarial Nets

224 citations · 3.2k across the 170 of their papers we have counts for

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Showing 2021 · cs.CVShow all

8 papers · 2 filters

cs.CV2021★ 6 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.CV2021★ 1 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.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.CV2021★ 121 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.CV2021★ 5 cited

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…

cs.CV2021

Unsupervised Part Segmentation through Disentangling Appearance and Shape

Shilong Liu, Lei Zhang, Xiao Yang +2

We study the problem of unsupervised discovery and segmentation of object parts, which, as an intermediate local representation, are capable of finding intrinsic object structure a…

cs.CV2021★ 7 cited

Rethinking Natural Adversarial Examples for Classification Models

Xiao Li, Jianmin Li, Ting Dai +3

Recently, it was found that many real-world examples without intentional modifications can fool machine learning models, and such examples are called "natural adversarial examples"…

cs.CV2021★ 4 cited

Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation

Qijun Luo, Zhili Liu, Lanqing Hong +7

Semi-supervised domain adaptation (SSDA), which aims to learn models in a partially labeled target domain with the assistance of the fully labeled source domain, attracts increasin…