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20242026
most citedRAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Towards Effective and Transferable Physical Camouflage against Multi-View BEV-based 3D Perception in Autonomous Driving

Linye Lyu, Jiawei Zhou, Daojing He +1

Modern autonomous driving systems widely adopt multi-view Bird's-Eye-View (BEV) based 3D perception models due to their superior performance. Despite their success, the robustness…

cs.CV2026

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…

cs.CV2025

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…

cs.CR2025

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…

cs.CV2024

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…

cs.CV2024

CNCA: Toward Customizable and Natural Generation of Adversarial Camouflage for Vehicle Detectors

Linye Lyu, Jiawei Zhou, Daojing He +1

Prior works on physical adversarial camouflage against vehicle detectors mainly focus on the effectiveness and robustness of the attack. The current most successful methods optimiz…

cs.CV2024★ 1 cited

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…