11 citations · 12 across the 8 of their papers we have counts for
6 papers · 1 filter
Multi-objective Evolutionary Search of Variable-length Composite Semantic Perturbations
Jialiang Sun, Wen Yao, Tingsong Jiang +1
Deep neural networks have proven to be vulnerable to adversarial attacks in the form of adding specific perturbations on images to make wrong outputs. Designing stronger adversaria…
RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World
Donghua Wang, Wen Yao, Tingsong Jiang +2
Physical adversarial attacks against deep neural networks (DNNs) have recently gained increasing attention. The current mainstream physical attacks use printed adversarial patches…
A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications
Donghua Wang, Wen Yao, Tingsong Jiang +3
Wide deployment of deep neural networks (DNNs) based applications (e.g., style transfer, cartoonish), stimulating the requirement of copyright protection of such application's prod…
Efficient Search of Comprehensively Robust Neural Architectures via Multi-fidelity Evaluation
Jialiang Sun, Wen Yao, Tingsong Jiang +1
Neural architecture search (NAS) has emerged as one successful technique to find robust deep neural network (DNN) architectures. However, most existing robustness evaluations in NA…
Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World
Chengyin Hu, Weiwen Shi, Tingsong Jiang +3
Infrared imaging systems have a vast array of potential applications in pedestrian detection and autonomous driving, and their safety performance is of great concern. However, few…
Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation
Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong +3
Few-shot segmentation enables the model to recognize unseen classes with few annotated examples. Most existing methods adopt prototype learning architecture, where support prototyp…