1 citations · 1 across the 3 of their papers we have counts for
4 papers
DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
Yun Xing, Yue Cao, Nhat Chung +6
Stereo depth estimation is a critical task in autonomous driving and robotics, where inaccuracies (such as misidentifying nearby objects as distant) can lead to dangerous situation…
MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents
Yun Xing, Nhat Chung, Jie Zhang +5
Physical adversarial attacks in driving scenarios can expose critical vulnerabilities in visual perception models. However, developing such attacks remains challenging due to diver…
SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments
Yue Cao, Yun Xing, Jie Zhang +5
Large vision-language models (LVLMs) have shown remarkable capabilities in interpreting visual content. While existing works demonstrate these models' vulnerability to deliberately…
CBVS: A Large-Scale Chinese Image-Text Benchmark for Real-World Short Video Search Scenarios
Xiangshuo Qiao, Xianxin Li, Xiaozhe Qu +5
Vision-Language Models pre-trained on large-scale image-text datasets have shown superior performance in downstream tasks such as image retrieval. Most of the images for pre-traini…