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08/22/2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging
Fast Adversarial Training (FAT) not only improves the model robustness b...
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07/24/2023
COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts
Practical object detection application can lose its effectiveness on ima...
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07/24/2023
Robust Automatic Speech Recognition via WavAugment Guided Phoneme Adversarial Training
Developing a practically-robust automatic speech recognition (ASR) is ch...
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07/10/2023
Learning Fine Pinch-Grasp Skills using Tactile Sensing from Real Demonstration Data
This work develops a data-efficient learning from demonstration framewor...
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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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11/29/2022
Context-Aware Robust Fine-Tuning
Contrastive Language-Image Pre-trained (CLIP) models have zero-shot abil...
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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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10/15/2021
Adversarial Attacks on ML Defense Models Competition
Due to the vulnerability of deep neural networks (DNNs) to adversarial e...
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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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04/06/2021
Fine-Grained Fashion Similarity Prediction by Attribute-Specific Embedding Learning
This paper strives to predict fine-grained fashion similarity. In this s...
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03/11/2021
Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink
Though it is well known that the performance of deep neural networks (DN...
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02/23/2021
Adversarial Examples Detection beyond Image Space
Deep neural networks have been proved that they are vulnerable to advers...
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12/10/2020
Composite Adversarial Attacks
Adversarial attack is a technique for deceiving Machine Learning (ML) mo...
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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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06/09/2020
GAP++: Learning to generate target-conditioned adversarial examples
Adversarial examples are perturbed inputs which can cause a serious thre...
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11/15/2019
Learning To Characterize Adversarial Subspaces
Deep Neural Networks (DNNs) are known to be vulnerable to the maliciousl...
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11/15/2019
Self-supervised Adversarial Training
Recent work has demonstrated that neural networks are vulnerable to adve...
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03/18/2019
