3 papers
cs.CV2024
Imperceptible Adversarial Examples in the Physical World
Weilin Xu, Sebastian Szyller, Cory Cornelius +5
Adversarial examples in the digital domain against deep learning-based computer vision models allow for perturbations that are imperceptible to human eyes. However, producing simil…
cs.CV2024
Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation
Kevin Stangl, Marius Arvinte, Weilin Xu +1
Zero-shot anomaly segmentation using pre-trained foundation models is a promising approach that enables effective algorithms without expensive, domain-specific training or fine-tun…
cs.LG2023
Investigating the Adversarial Robustness of Density Estimation Using the Probability Flow ODE
Marius Arvinte, Cory Cornelius, Jason Martin +1
Beyond their impressive sampling capabilities, score-based diffusion models offer a powerful analysis tool in the form of unbiased density estimation of a query sample under the tr…