5 papers · 1 filter
Can NeRFs See without Cameras?
Chaitanya Amballa, Sattwik Basu, Yu-Lin Wei +3
Neural Radiance Fields (NeRFs) have been remarkably successful at synthesizing novel views of 3D scenes by optimizing a volumetric scene function. This scene function models how op…
AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models
Tommy Nguyen, Mehmet Ergezer, Christian Green
The increasing deployment of AI models in critical applications has exposed them to significant risks from adversarial attacks. While adversarial vulnerabilities in 2D vision model…
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…
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…
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…