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03/30/2023
ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing
Recent studies have shown that higher accuracy on ImageNet usually leads...
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03/28/2023
TransAudio: Towards the Transferable Adversarial Audio Attack via Learning Contextualized Perturbations
In a transfer-based attack against Automatic Speech Recognition (ASR) sy...
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03/21/2023
Information-containing Adversarial Perturbation for Combating Facial Manipulation Systems
With the development of deep learning technology, the facial manipulatio...
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11/30/2022
Rethinking Out-of-Distribution Detection From a Human-Centric Perspective
Out-Of-Distribution (OOD) detection has received broad attention over th...
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10/09/2022
Boosting Out-of-distribution Detection with Typical Features
Out-of-distribution (OOD) detection is a critical task for ensuring the ...
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09/16/2022
Enhance the Visual Representation via Discrete Adversarial Training
Adversarial Training (AT), which is commonly accepted as one of the most...
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05/17/2021
Rethinking the Design Principles of Robust Vision Transformer
Recent advances on Vision Transformers (ViT) have shown that self-attent...
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03/04/2021
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
We study the query-based attack against image retrieval to evaluate its ...
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03/02/2021
Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
The remarkable success in face forgery techniques has received considera...
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08/11/2020
Sharp Multiple Instance Learning for DeepFake Video Detection
With the rapid development of facial manipulation techniques, face forge...
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11/15/2019
AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
Deep neural networks have been shown to be vulnerable to adversarial exa...
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12/29/2017