FRE: A Fast Method For Anomaly Detection And Segmentation

no code implementations • 23 Nov 2022 • Ibrahima Ndiour, Nilesh Ahuja, Utku Genc, Omesh Tickoo

This paper presents a fast and principled approach for solving the visual anomaly detection and segmentation problem.

Anomaly Detection Dimensionality Reduction

Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features

no code implementations • 8 Dec 2020 • Ibrahima Ndiour, Nilesh Ahuja, Omesh Tickoo

We also show that the feature reconstruction error, which is the $L_2$-norm of the difference between the original feature and the pre-image of its embedding, is highly effective for OOD detection and in some cases superior to the log-likelihood scores.

Dimensionality Reduction Out-of-Distribution Detection +1

Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection

no code implementations • 25 Sep 2019 • Nilesh A. Ahuja, Ibrahima Ndiour, Trushant Kalyanpur, Omesh Tickoo

We present a principled approach for detecting out-of-distribution (OOD) and adversarial samples in deep neural networks.

Adversarial Attack