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07/20/2023
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples
Backdoor attacks are serious security threats to machine learning models...
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07/14/2023
Boosting Backdoor Attack with A Learnable Poisoning Sample Selection Strategy
Data-poisoning based backdoor attacks aim to insert backdoor into models...
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07/07/2023
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
3D facial avatar reconstruction has been a significant research topic in...
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07/04/2023
DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection
A critical yet frequently overlooked challenge in the field of deepfake ...
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06/29/2023
Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features
Recent studies have demonstrated the susceptibility of deep neural netwo...
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06/01/2023
Robust Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers
Deep neural networks (DNNs) can be manipulated to exhibit specific behav...
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05/28/2023
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Data-free meta-learning (DFML) aims to enable efficient learning of new ...
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05/11/2023
Inter-frame Accelerate Attack against Video Interpolation Models
Deep learning based video frame interpolation (VIF) method, aiming to sy...
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04/27/2023
UCF: Uncovering Common Features for Generalizable Deepfake Detection
Deepfake detection remains a challenging task due to the difficulty of g...
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04/24/2023
Enhancing Fine-Tuning Based Backdoor Defense with Sharpness-Aware Minimization
Backdoor defense, which aims to detect or mitigate the effect of malicio...
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04/02/2023
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks
In this paper, we study masked autoencoder (MAE) pretraining on videos f...
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04/01/2023
Improving Fast Adversarial Training with Prior-Guided Knowledge
Fast adversarial training (FAT) is an efficient method to improve robust...
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03/15/2023
Visual Prompt Based Personalized Federated Learning
As a popular paradigm of distributed learning, personalized federated le...
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02/19/2023
Adversarial Machine Learning: A Systematic Survey of Backdoor Attack, Weight Attack and Adversarial Example
Adversarial machine learning (AML) studies the adversarial phenomenon of...
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11/03/2022
Physically Adversarial Attacks and Defenses in Computer Vision: A Survey
Although Deep Neural Networks (DNNs) have been widely applied in various...
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10/31/2022
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning
The permutation flow shop scheduling (PFSS), aiming at finding the optim...
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10/12/2022
Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation
Deep neural networks (DNNs) have been shown to be vulnerable to adversar...
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10/02/2022
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis
Adversarial Training (AT) has been demonstrated as one of the most effec...
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09/16/2022
A Large-scale Multiple-objective Method for Black-box Attack against Object Detection
Recent studies have shown that detectors based on deep models are vulner...
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08/17/2022
Imperceptible and Robust Backdoor Attack in 3D Point Cloud
With the thriving of deep learning in processing point cloud data, recen...
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07/25/2022
Versatile Weight Attack via Flipping Limited Bits
To explore the vulnerability of deep neural networks (DNNs), many attack...
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07/18/2022
Prior-Guided Adversarial Initialization for Fast Adversarial Training
Fast adversarial training (FAT) effectively improves the efficiency of s...
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07/05/2022
Learning to Accelerate Approximate Methods for Solving Integer Programming via Early Fixing
Integer programming (IP) is an important and challenging problem. Approx...
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06/25/2022
BackdoorBench: A Comprehensive Benchmark of Backdoor Learning
Backdoor learning is an emerging and important topic of studying the vul...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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03/13/2022
LAS-AT: Adversarial Training with Learnable Attack Strategy
Adversarial training (AT) is always formulated as a minimax problem, of ...
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03/08/2022
StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pretrained StyleGAN
One-shot talking face generation aims at synthesizing a high-quality tal...
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02/05/2022
Backdoor Defense via Decoupling the Training Process
Recent studies have revealed that deep neural networks (DNNs) are vulner...
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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...
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10/11/2021
Boosting Fast Adversarial Training with Learnable Adversarial Initialization
Adversarial training (AT) has been demonstrated to be effective in impro...
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09/20/2021
Robust Physical-World Attacks on Face Recognition
Face recognition has been greatly facilitated by the development of deep...
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09/02/2021
Regional Adversarial Training for Better Robust Generalization
Adversarial training (AT) has been demonstrated as one of the most promi...
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05/17/2021
Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
Due to its powerful capability of representation learning and high-effic...
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04/23/2021
Theoretical Study of Random Noise Defense against Query-Based Black-Box Attacks
The query-based black-box attacks, which don't require any knowledge abo...
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04/21/2021
Towards Corruption-Agnostic Robust Domain Adaptation
Big progress has been achieved in domain adaptation in decades. Existing...
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04/18/2021
Towards Open-World Text-Guided Face Image Generation and Manipulation
The existing text-guided image synthesis methods can only produce limite...
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03/09/2021
Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation
To generate "accurate" scene graphs, almost all existing methods predict...
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02/21/2021
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
To explore the vulnerability of deep neural networks (DNNs), many attack...
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02/19/2021
Effective and Efficient Vote Attack on Capsule Networks
Standard Convolutional Neural Networks (CNNs) can be easily fooled by im...
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12/07/2020
Backdoor Attack with Sample-Specific Triggers
Recently, backdoor attacks pose a new security threat to the training pr...
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12/06/2020
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
In this work, we propose TediGAN, a novel framework for multi-modal imag...
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11/09/2020
Dual ResGCN for Balanced Scene GraphGeneration
Visual scene graph generation is a challenging task. Previous works have...
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11/04/2020
Pixel-wise Dense Detector for Image Inpainting
Recent GAN-based image inpainting approaches adopt an average strategy t...
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10/19/2020
Teacher-Student Competition for Unsupervised Domain Adaptation
With the supervision from source domain only in class-level, existing un...
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08/16/2020
SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Although significant progress achieved, multi-label classification is st...
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07/17/2020
Backdoor Learning: A Survey
Deep neural networks (DNNs) have demonstrated their power on many widely...
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06/15/2020
Efficient Black-Box Adversarial Attack Guided by the Distribution of Adversarial Perturbations
This work studied the score-based black-box adversarial attack problem, ...
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05/12/2020
Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients
Adversarial examples have been well known as a serious threat to deep ne...
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04/09/2020
Rethinking the Trigger of Backdoor Attack
In this work, we study the problem of backdoor attacks, which add a spec...
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03/16/2020
