activity
20242026
collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2025

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…

cs.CV2024

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…

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…