activity
20232025
most citedSceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Beyond Pixels: Semantic-aware Typographic Attack for Geo-Privacy Protection

Jiayi Zhu, Yihao Huang, Yue Cao +5

Large Visual Language Models (LVLMs) now pose a serious yet overlooked privacy threat, as they can infer a social media user's geolocation directly from shared images, leading to u…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2023

IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks

Yue Cao, Tianlin Li, Xiaofeng Cao +3

We introduce a novel approach to counter adversarial attacks, namely, image resampling. Image resampling transforms a discrete image into a new one, simulating the process of scene…