34 citations · 130 across the 35 of their papers we have counts for
12 papers · 1 filter
Towards Black-box Adversarial Example Detection: A Data Reconstruction-based Method
Yifei Gao, Zhiyu Lin, Yunfan Yang +1
Adversarial example detection is known to be an effective adversarial defense method. Black-box attack, which is a more realistic threat and has led to various black-box adversaria…
Improved Visual Fine-tuning with Natural Language Supervision
Junyang Wang, Yuanhong Xu, Juhua Hu +3
Fine-tuning a visual pre-trained model can leverage the semantic information from large-scale pre-training data and mitigate the over-fitting problem on downstream vision tasks wit…
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment
Junyang Wang, Yi Zhang, Ming Yan +2
CLIP (Contrastive Language-Image Pre-Training) has shown remarkable zero-shot transfer capabilities in cross-modal correlation tasks such as visual classification and image retriev…
FairCLIP: Social Bias Elimination based on Attribute Prototype Learning and Representation Neutralization
Junyang Wang, Yi Zhang, Jitao Sang
The Vision-Language Pre-training (VLP) models like CLIP have gained popularity in recent years. However, many works found that the social biases hidden in CLIP easily manifest in d…
Counterfactually Measuring and Eliminating Social Bias in Vision-Language Pre-training Models
Yi Zhang, Junyang Wang, Jitao Sang
Vision-Language Pre-training (VLP) models have achieved state-of-the-art performance in numerous cross-modal tasks. Since they are optimized to capture the statistical properties o…
Low-Mid Adversarial Perturbation against Unauthorized Face Recognition System
Jiaming Zhang, Qi Yi, Dongyuan Lu +1
In light of the growing concerns regarding the unauthorized use of facial recognition systems and its implications on individual privacy, the exploration of adversarial perturbatio…
Investigating and Explaining the Frequency Bias in Image Classification
Zhiyu Lin, Yifei Gao, Jitao Sang
CNNs exhibit many behaviors different from humans, one of which is the capability of employing high-frequency components. This paper discusses the frequency bias phenomenon in imag…
Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis
Yaogong Feng, Xiaowen Huang, Pengbo Yang +2
Synthesizing pseudo samples is currently the most effective way to solve the Generalized Zero-Shot Learning (GZSL) problem. Most models achieve competitive performance but still su…
ImageNet Pre-training also Transfers Non-Robustness
Jiaming Zhang, Jitao Sang, Qi Yi +3
ImageNet pre-training has enabled state-of-the-art results on many tasks. In spite of its recognized contribution to generalization, we observed in this study that ImageNet pre-tra…
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing
Yi Zhang, Jitao Sang
Machine learning fairness concerns about the biases towards certain protected or sensitive group of people when addressing the target tasks. This paper studies the debiasing proble…
Adaptive Adversarial Logits Pairing
Shangxi Wu, Jitao Sang, Kaiyuan Xu +2
Adversarial examples provide an opportunity as well as impose a challenge for understanding image classification systems. Based on the analysis of the adversarial training solution…
Attention, Please! Adversarial Defense via Activation Rectification and Preservation
Shangxi Wu, Jitao Sang, Kaiyuan Xu +2
This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change. In particular, we obs…