3 accepted papers
Physical adversarial attack methods expose the vulnerabilities of deep neural networks and pose a significant threat to safety-critical scenarios such as autonomous driving. Camouflage-based physical attack is a more promising approach compared to the patch-based attack, offering stronger adversaria…
Object detection is widely used in real-world applications such as autonomous driving, yet adversarial camouflage poses a significant threat by deceiving detectors from multiple viewpoints. Existing techniques struggle to maintain consistent attack efficacy across different viewpoints. To address th…
Adversarial attack methods based on point manipulation for 3D point cloud classification have revealed the fragility of 3D models yet the adversarial examples they produce are easily perceived or defended against. The trade-off between the imperceptibility and adversarial strength leads most point a…