No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection

12 June 2023

Papers citing "No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection"

10 / 10 papers shown

Title
Language-Assisted Feature Transformation for Anomaly Detection EungGu Yun Heonjin Ha Yeongwoo Nam Bryan Dongik Lee 63 0 0 03 Mar 2025
COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection Jingyi Liao Xun Xu Manh Cuong Nguyen A. Goodge Chuan-Sheng Foo 42 9 0 29 Feb 2024
Set Features for Anomaly Detection Niv Cohen Issar Tzachor Yedid Hoshen 32 0 0 24 Nov 2023
Don't Miss Out on Novelty: Importance of Novel Features for Deep Anomaly Detection S. Sivaprasad Mario Fritz AAML 24 0 0 01 Oct 2023
Representation Learning in Anomaly Detection: Successes, Limits and a Grand Challenge Yedid Hoshen UQCV 16 0 0 20 Jul 2023
SimpleNet: A Simple Network for Image Anomaly Detection and Localization Zhikang Liu Yiming Zhou Yuansheng Xu Zilei Wang 75 229 0 27 Mar 2023
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation Jongheon Jeong Yang Zou Taewan Kim Dongqing Zhang Avinash Ravichandran O. Dabeer VLM 75 186 0 26 Mar 2023
Anomaly Detection Requires Better Representations Tal Reiss Niv Cohen Eliahu Horwitz Ron Abutbul Yedid Hoshen OOD AI4TS SSL 46 21 0 19 Oct 2022
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization Hannah M. Schlüter Jeremy Tan Benjamin Hou Bernhard Kainz 118 128 0 30 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 326 5,785 0 29 Apr 2021