5 papers · 1 filter
Catch Me If You Can Describe Me: Open-Vocabulary Camouflaged Instance Segmentation with Diffusion
Tuan-Anh Vu, Duc Thanh Nguyen, Qing Guo +4
Text-to-image diffusion techniques have shown exceptional capabilities in producing high-quality, dense visual predictions from open-vocabulary text. This indicates a strong correl…
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…
FOCUS: Frequency-Optimized Conditioning of DiffUSion Models for mitigating catastrophic forgetting during Test-Time Adaptation
Gabriel Tjio, Jie Zhang, Xulei Yang +6
Test-time adaptation enables models to adapt to evolving domains. However, balancing the tradeoff between preserving knowledge and adapting to domain shifts remains challenging for…
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…
Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography
Nhat Chung, Sensen Gao, Tuan-Anh Vu +5
Vision-Large-Language-Models (Vision-LLMs) are increasingly being integrated into autonomous driving (AD) systems due to their advanced visual-language reasoning capabilities, targ…