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05/22/2023
Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks
Physical world adversarial attack is a highly practical and threatening ...
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02/19/2023
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection
Adversarial attacks are valuable for evaluating the robustness of deep l...
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11/19/2022
Phonemic Adversarial Attack against Audio Recognition in Real World
Recently, adversarial attacks for audio recognition have attracted much ...
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08/23/2022
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection
Billions of people are sharing their daily life images on social media e...
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04/13/2022
Defensive Patches for Robust Recognition in the Physical World
To operate in real-world high-stakes environments, deep learning systems...
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09/16/2021
Harnessing Perceptual Adversarial Patches for Crowd Counting
Crowd counting, which is significantly important for estimating the numb...
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09/11/2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
Deep neural networks (DNNs) are vulnerable to adversarial noises, which ...
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09/01/2021
Diverse Sample Generation: Pushing the Limit of Data-free Quantization
Recently, generative data-free quantization emerges as a practical appro...
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08/23/2021
Towards Real-world X-ray Security Inspection: A High-Quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection
Prohibited items detection in X-ray images often plays an important role...
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03/01/2021
Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
Deep learning models are vulnerable to adversarial examples. As a more t...
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01/24/2021
A Comprehensive Evaluation Framework for Deep Model Robustness
Deep neural networks (DNNs) have achieved remarkable performance across ...
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05/19/2020
