b'Xingxing Wei'

research

∙ 08/16/2023

Classification Committee for Active Deep Object Detection

In object detection, the cost of labeling is much high because it needs ...

0 Lei Zhao, et al. ∙

research

∙ 07/27/2023

Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical World

Physical adversarial attacks have put a severe threat to DNN-based objec...

0 Xingxing Wei, et al. ∙

research

∙ 07/26/2023

Defending Adversarial Patches via Joint Region Localizing and Inpainting

Deep neural networks are successfully used in various applications, but ...

0 Junwen Chen, et al. ∙

research

∙ 07/21/2023

Improving Viewpoint Robustness for Visual Recognition via Adversarial Training

Viewpoint invariance remains challenging for visual recognition in the 3...

0 Shouwei Ruan, et al. ∙

research

∙ 07/15/2023

Unified Adversarial Patch for Cross-modal Attacks in the Physical World

Recently, physical adversarial attacks have been presented to evade DNNs...

0 Xingxing Wei, et al. ∙

research

∙ 07/03/2023

Structured Network Pruning by Measuring Filter-wise Interactions

Structured network pruning is a practical approach to reduce computation...

0 Wenting Tang, et al. ∙

research

∙ 06/28/2023

Learning to Pan-sharpening with Memories of Spatial Details

Pan-sharpening, as one of the most commonly used techniques in remote se...

0 Maoxun Yuan, et al. ∙

research

∙ 06/28/2023

𝐂^2Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection

Object detection on visible (RGB) and infrared (IR) images, as an emergi...

0 Maoxun Yuan, et al. ∙

research

∙ 06/28/2023

Mitigating the Accuracy-Robustness Trade-off via Multi-Teacher Adversarial Distillation

Adversarial training is a practical approach for improving the robustnes...

0 Shiji Zhao, et al. ∙

research

∙ 06/28/2023

Distributional Modeling for Location-Aware Adversarial Patches

Adversarial patch is one of the important forms of performing adversaria...

0 Xingxing Wei, et al. ∙

research

∙ 06/28/2023

Boosting Adversarial Transferability with Learnable Patch-wise Masks

Adversarial examples have raised widespread attention in security-critic...

0 Xingxing Wei, et al. ∙

research

∙ 06/15/2023

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks in the Physical World

Adversarial attacks in the physical world, particularly patch attacks, p...

0 Caixin Kang, et al. ∙

research

∙ 06/06/2023

Revisiting the Trade-off between Accuracy and Robustness via Weight Distribution of Filters

Adversarial attacks have been proven to be potential threats to Deep Neu...

0 Xingxing Wei, et al. ∙

research

∙ 04/01/2023

Improving Fast Adversarial Training with Prior-Guided Knowledge

Fast adversarial training (FAT) is an efficient method to improve robust...

0 Xiaojun Jia, et al. ∙

research

∙ 03/20/2023

Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving

3D object detection is an important task in autonomous driving to percei...

0 Yinpeng Dong, et al. ∙

research

∙ 03/17/2023

MedLocker: A Transferable Adversarial Watermarking for Preventing Unauthorized Analysis of Medical Image Dataset

The collection of medical image datasets is a demanding and laborious pr...

12 Bangzheng Pu, et al. ∙

research

∙ 12/26/2022

Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch Attacks

Adversarial patch is an important form of real-world adversarial attack ...

0 Xingxing Wei, et al. ∙

research

∙ 11/03/2022

Physically Adversarial Attacks and Defenses in Computer Vision: A Survey

Although Deep Neural Networks (DNNs) have been widely applied in various...

0 Xingxing Wei, et al. ∙

research

∙ 10/08/2022

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints

Recent studies have demonstrated that visual recognition models lack rob...

0 Yinpeng Dong, et al. ∙

research

∙ 09/28/2022

Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection

Integrating multispectral data in object detection, especially visible a...

0 Maoxun Yuan, et al. ∙

research

∙ 07/18/2022

Prior-Guided Adversarial Initialization for Fast Adversarial Training

Fast adversarial training (FAT) effectively improves the efficiency of s...

0 Xiaojun Jia, et al. ∙

research

∙ 03/25/2022

Improving Adversarial Transferability with Spatial Momentum

Deep Neural Networks (DNN) are vulnerable to adversarial examples. Altho...

0 Guoqiu Wang, et al. ∙

research

∙ 01/22/2022

Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection

Object detection has been widely used in many safety-critical tasks, suc...

0 Siyuan Liang, et al. ∙

research

∙ 08/01/2021

An Effective and Robust Detector for Logo Detection

In recent years, intellectual property (IP), which represents literary, ...

0 Xiaojun Jia, et al. ∙

research

∙ 05/11/2021

Improving Adversarial Transferability with Gradient Refining

Deep neural networks are vulnerable to adversarial examples, which are c...

0 Guoqiu Wang, et al. ∙

research

∙ 04/14/2021

Meaningful Adversarial Stickers for Face Recognition in Physical World

Face recognition (FR) systems have been widely applied in safety-critica...

0 Ying Guo, et al. ∙

research

∙ 11/12/2020

Automated Model Compression by Jointly Applied Pruning and Quantization

In the traditional deep compression framework, iteratively performing ne...

0 Wenting Tang, et al. ∙

research

∙ 10/28/2020

Object Hider: Adversarial Patch Attack Against Object Detectors

Deep neural networks have been widely used in many computer vision tasks...

0 Yusheng Zhao, et al. ∙

research

∙ 08/05/2020

Adv-watermark: A Novel Watermark Perturbation for Adversarial Examples

Recent research has demonstrated that adding some imperceptible perturba...

0 Xiaojun Jia, et al. ∙

research

∙ 08/01/2020

Efficient Adversarial Attacks for Visual Object Tracking

Visual object tracking is an important task that requires the tracker to...

0 Siyuan Liang, et al. ∙

research

∙ 05/27/2020

Attention: to Better Stand on the Shoulders of Giants

Science of science (SciSci) is an emerging discipline wherein science is...

18 Sha Yuan, et al. ∙

research

∙ 01/11/2020

Sparse Black-box Video Attack with Reinforcement Learning

Adversarial attacks on video recognition models have been explored recen...

14 Huanqian Yan, et al. ∙

research

∙ 11/21/2019

Heuristic Black-box Adversarial Attacks on Video Recognition Models

We study the problem of attacking video recognition models in the black-...

0 Zhipeng Wei, et al. ∙

research

∙ 09/11/2019

Identifying and Resisting Adversarial Videos Using Temporal Consistency

Video classification is a challenging task in computer vision. Although ...

0 Xiaojun Jia, et al. ∙

research

∙ 05/29/2019

Automatic Realistic Music Video Generation from Segments of Youtube Videos

A Music Video (MV) is a video aiming at visually illustrating or extendi...

0 Sarah Gross, et al. ∙

research

∙ 11/30/2018

ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples

Deep neural networks (DNNs) have been demonstrated to be vulnerable to a...

0 Xiaojun Jia, et al. ∙

research

∙ 11/30/2018

Transferable Adversarial Attacks for Image and Video Object Detection

Adversarial examples have been demonstrated to threaten many computer vi...

8 Xingxing Wei, et al. ∙

research

∙ 11/06/2018

Modeling and Predicting Popularity Dynamics via Deep Learning Attention Mechanism

An ability to predict the popularity dynamics of individual items within...

0 Sha Yuan, et al. ∙

research

∙ 03/07/2018

Sparse Adversarial Perturbations for Videos

Although adversarial samples of deep neural networks (DNNs) have been in...

0 Xingxing Wei, et al. ∙

Xingxing Wei

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