327 citations · 466 across the 16 of their papers we have counts for
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3 papers · 1 filter
cs.CV2023★ 1 cited
Set Features for Anomaly Detection
Niv Cohen, Issar Tzachor, Yedid Hoshen
This paper proposes to use set features for detecting anomalies in samples that consist of unusual combinations of normal elements. Many leading methods discover anomalies by detec…
cs.LG2023★ 1 cited
No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection
Tal Reiss, Niv Cohen, Yedid Hoshen
Anomaly detection methods, powered by deep learning, have recently been making significant progress, mostly due to improved representations. It is tempting to hypothesize that anom…
cs.CV2023★ 12 cited
Set Features for Fine-grained Anomaly Detection
Niv Cohen, Issar Tzachor, Yedid Hoshen
Fine-grained anomaly detection has recently been dominated by segmentation based approaches. These approaches first classify each element of the sample (e.g., image patch) as norma…