3 papers
cs.CV2024
Targeted View-Invariant Adversarial Perturbations for 3D Object Recognition
Christian Green, Mehmet Ergezer, Abdurrahman Zeybey
Adversarial attacks pose significant challenges in 3D object recognition, especially in scenarios involving multi-view analysis where objects can be observed from varying angles. T…
cs.CV2024
Gaussian Splatting Under Attack: Investigating Adversarial Noise in 3D Objects
Abdurrahman Zeybey, Mehmet Ergezer, Tommy Nguyen
3D Gaussian Splatting has advanced radiance field reconstruction, enabling high-quality view synthesis and fast rendering in 3D modeling. While adversarial attacks on object detect…
cs.CV2024
One Noise to Rule Them All: Multi-View Adversarial Attacks with Universal Perturbation
Mehmet Ergezer, Phat Duong, Christian Green +2
This paper presents a novel universal perturbation method for generating robust multi-view adversarial examples in 3D object recognition. Unlike conventional attacks limited to sin…