110 citations · 209 across the 2 of their papers we have counts for
3 papers
cs.CV2020
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Tal Reiss, Niv Cohen, Liron Bergman +1
Anomaly detection methods require high-quality features. In recent years, the anomaly detection community has attempted to obtain better features using advances in deep self-superv…
cs.LG2020★ 99 cited
Classification-Based Anomaly Detection for General Data
Liron Bergman, Yedid Hoshen
Anomaly detection, finding patterns that substantially deviate from those seen previously, is one of the fundamental problems of artificial intelligence. Recently, classification-b…
cs.LG2020★ 110 cited
Deep Nearest Neighbor Anomaly Detection
Liron Bergman, Niv Cohen, Yedid Hoshen
Nearest neighbors is a successful and long-standing technique for anomaly detection. Significant progress has been recently achieved by self-supervised deep methods (e.g. RotNet).…