5 papers
Toward Physically Consistent Driving Video World Models under Challenging Trajectories
Jiawei Zhou, Zhenxin Zhu, Lingyi Du +10
Video generation models have shown strong potential as world models for autonomous driving simulation. However, existing approaches are primarily trained on real-world driving data…
SWA-LDM: Toward Stealthy Watermarks for Latent Diffusion Models
Zhonghao Yang, Linye Lyu, Xuanhang Chang +2
Latent Diffusion Models (LDMs) have established themselves as powerful tools in the rapidly evolving field of image generation, capable of producing highly realistic images. Howeve…
Toward Robust and Accurate Adversarial Camouflage Generation against Vehicle Detectors
Jiawei Zhou, Linye Lyu, Daojing He +1
Adversarial camouflage is a widely used physical attack against vehicle detectors for its superiority in multi-view attack performance. One promising approach involves using differ…
SafeMVDrive: Multi-view Safety-Critical Driving Video Synthesis in the Real World Domain
Jiawei Zhou, Linye Lyu, Zhuotao Tian +2
Safety-critical scenarios are rare yet pivotal for evaluating and enhancing the robustness of autonomous driving systems. While existing methods generate safety-critical driving tr…
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
Jiawei Zhou, Linye Lyu, Daojing He +1
Adversarial camouflage is a widely used physical attack against vehicle detectors for its superiority in multi-view attack performance. One promising approach involves using differ…