Adversarial Robustness of Camera-Radar Sensor Fusion for Autonomous Driving
Autonomous driving (AD) relies on multi-sensor perception to interpret the surrounding environment. However, the robustness of camera--radar fusion under adversarial conditions remains largely unexplored. This paper presents a systematic measurement study of the robustness of camera--radar sensor fusion in AD. We construct a unified evaluation pipeline on the nuScenes dataset that simulates attacks on both sensing modalities, including eight camera-image perturbations and three radar point-cloud perturbations. We evaluate five camera--radar fusion algorithms across two perception tasks, 3D object detection and depth estimation, and quantify their performance under clean and attacked input...
| Authors | Ce Zhou, Yubo Wu, Khang Nguyen et al. |
|---|---|
| Primary category | cs.CR |
| Published | 12 October 2026 |
| Last updated at source | 12 October 2026 |
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