5 papers
AdvTiles: Physical Adversarial Camouflage Clothing against Person Detectors via Learnable Tiles
Jinlei Wang, Jiahuan Long, Mingkai Sun +9
Physical adversarial attacks against person detectors have evolved from localized patches to full-body textures. However, achieving both visual naturalness and strong attack effect…
When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models
Jiacheng Hou, Yining Sun, Ruochong Jin +4
Recent advances in large image editing models have shifted the paradigm from text-driven instructions to vision-prompt editing, where user intent is inferred directly from visual i…
JailWAM: Jailbreaking World Action Models in Robot Control
Hanqing Liu, Songping Wang, Jiahuan Long +9
World Action Models (WAMs) have emerged as a promising paradigm for robotic manipulation, enabling physical interaction across diverse tasks and environments. However, their abilit…
Eva-VLA: Evaluating Vision-Language-Action Models' Robustness Under Real-World Physical Variations
Hanqing Liu, Shouwei Ruan, Jiahuan Long +6
Vision-Language-Action (VLA) models have emerged as promising solutions for robotic manipulation, yet their robustness to real-world physical variations remains critically underexp…
CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors
Jiahuan Long, Wen Yao, Tingsong Jiang +1
Adversarial patches are widely used to evaluate the robustness of object detection systems in real-world scenarios. These patches were initially designed to deceive single-modal de…