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09/21/2023
How Robust is Google's Bard to Adversarial Image Attacks?
Multimodal Large Language Models (MLLMs) that integrate text and other m...
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09/05/2023
Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
The rise of deepfake images, especially of well-known personalities, pos...
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08/24/2023
Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Vision-language pre-training models (VLP) are vulnerable, especially to ...
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08/19/2023
Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos
This work focuses on the 3D reconstruction of non-rigid objects based on...
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07/21/2023
Improving Viewpoint Robustness for Visual Recognition via Adversarial Training
Viewpoint invariance remains challenging for visual recognition in the 3...
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06/28/2023
Distributional Modeling for Location-Aware Adversarial Patches
Adversarial patch is one of the important forms of performing adversaria...
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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...
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05/24/2023
Robust Classification via a Single Diffusion Model
Recently, diffusion models have been successfully applied to improving a...
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05/07/2023
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning
With the help of conditioning mechanisms, the state-of-the-art diffusion...
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04/20/2023
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
Large-scale pre-trained models have achieved remarkable success in a var...
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03/30/2023
Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving
3D object detection is an essential perception task in autonomous drivin...
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03/28/2023
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition
Face recognition is a prevailing authentication solution in numerous bio...
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03/25/2023
Compacting Binary Neural Networks by Sparse Kernel Selection
Binary Neural Network (BNN) represents convolution weights with 1-bit va...
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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...
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03/16/2023
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
Deep learning models are vulnerable to adversarial examples. Transfer-ba...
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02/28/2023
GNOT: A General Neural Operator Transformer for Operator Learning
Learning partial differential equations' (PDEs) solution operators is an...
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12/07/2022
Artificial Intelligence Security Competition (AISC)
The security of artificial intelligence (AI) is an important research ar...
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11/02/2022
Improving transferability of 3D adversarial attacks with scale and shear transformations
Previous work has shown that 3D point cloud classifiers can be vulnerabl...
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10/27/2022
Isometric 3D Adversarial Examples in the Physical World
3D deep learning models are shown to be as vulnerable to adversarial exa...
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10/08/2022
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
Recent studies have demonstrated that visual recognition models lack rob...
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10/07/2022
Pre-trained Adversarial Perturbations
Self-supervised pre-training has drawn increasing attention in recent ye...
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06/09/2022
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing
Certified defenses such as randomized smoothing have shown promise towar...
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06/03/2022
Kallima: A Clean-label Framework for Textual Backdoor Attacks
Although Deep Neural Network (DNN) has led to unprecedented progress in ...
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05/28/2022
BadDet: Backdoor Attacks on Object Detection
Deep learning models have been deployed in numerous real-world applicati...
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03/13/2022
Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior
Adversarial attacks have been extensively studied in recent years since ...
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03/09/2022
Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition
Recent studies have revealed the vulnerability of face recognition model...
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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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10/13/2021
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness
The vulnerability of deep neural networks to adversarial examples has mo...
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07/05/2021
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks
Transfer-based adversarial attacks can effectively evaluate model robust...
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06/29/2021
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Face recognition is greatly improved by deep convolutional neural networ...
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06/18/2021
Accumulative Poisoning Attacks on Real-time Data
Collecting training data from untrusted sources exposes machine learning...
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06/03/2021
Exploring Memorization in Adversarial Training
It is well known that deep learning models have a propensity for fitting...
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05/31/2021
Adversarial Training with Rectified Rejection
Adversarial training (AT) is one of the most effective strategies for pr...
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05/09/2021
Automated Decision-based Adversarial Attacks
Deep learning models are vulnerable to adversarial examples, which can f...
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03/24/2021
Black-box Detection of Backdoor Attacks with Limited Information and Data
Although deep neural networks (DNNs) have made rapid progress in recent ...
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10/01/2020
Bag of Tricks for Adversarial Training
Adversarial training (AT) is one of the most effective strategies for pr...
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07/08/2020
Delving into the Adversarial Robustness on Face Recognition
Face recognition has recently made substantial progress and achieved hig...
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03/15/2020
Towards Privacy Protection by Generating Adversarial Identity Masks
As billions of personal data such as photos are shared through social me...
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02/20/2020
Boosting Adversarial Training with Hypersphere Embedding
Adversarial training (AT) is one of the most effective defenses to impro...
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02/14/2020
Adversarial Distributional Training for Robust Deep Learning
Adversarial training (AT) is among the most effective techniques to impr...
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12/26/2019
Benchmarking Adversarial Robustness
Deep neural networks are vulnerable to adversarial examples, which becom...
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06/17/2019
Improving Black-box Adversarial Attacks with a Transfer-based Prior
We consider the black-box adversarial setting, where the adversary has t...
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05/25/2019
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness
Previous work shows that adversarially robust generalization requires la...
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04/09/2019
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition
Face recognition has obtained remarkable progress in recent years due to...
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04/05/2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks
Deep neural networks are vulnerable to adversarial examples, which can m...
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02/25/2019
Batch Virtual Adversarial Training for Graph Convolutional Networks
We present batch virtual adversarial training (BVAT), a novel regulariza...
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01/25/2019
Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples
Sometimes it is not enough for a DNN to produce an outcome. For example,...
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11/16/2018
Composite Binary Decomposition Networks
Binary neural networks have great resource and computing efficiency, whi...
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06/13/2018
Learning Visual Knowledge Memory Networks for Visual Question Answering
Visual question answering (VQA) requires joint comprehension of images a...
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03/31/2018