Set Features for Fine-grained Anomaly Detection

Set Features for Fine-grained Anomaly Detection

23 February 2023

Papers citing "Set Features for Fine-grained Anomaly Detection"

12 / 12 papers shown

Title
Towards Training-free Anomaly Detection with Vision and Language Foundation Models Jinjin Zhang Guodong Wang Yizhou Jin Di Huang 42 1 0 24 Mar 2025
MiniMaxAD: A Lightweight Autoencoder for Feature-Rich Anomaly Detection Feng Wang Chengming Liu Lei Shi Haibo Pang 32 1 0 16 May 2024
LogicAL: Towards logical anomaly synthesis for unsupervised anomaly localization Ying Zhao 34 6 0 11 May 2024
PUAD: Frustratingly Simple Method for Robust Anomaly Detection S. Sugawara Ryuji Imamura 28 3 0 23 Feb 2024
Generating and Reweighting Dense Contrastive Patterns for Unsupervised Anomaly Detection Songmin Dai Yifan Wu Xiaoqiang Li Xiangyang Xue 25 12 0 26 Dec 2023
Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection Soopil Kim Sion An Philip Chikontwe Myeongkyun Kang Ehsan Adeli K. Pohl Sanghyun Park 19 17 0 21 Dec 2023
REB: Reducing Biases in Representation for Industrial Anomaly Detection Shuai Lyu Dongmei Mo W. Wong 19 12 0 24 Aug 2023
Representation Learning in Anomaly Detection: Successes, Limits and a Grand Challenge Yedid Hoshen UQCV 16 0 0 20 Jul 2023
Component-aware anomaly detection framework for adjustable and logical industrial visual inspection Tongkun Liu Bing Li Xiao Du Bingke Jiang Xiao Jin Liuyi Jin Zhu Zhao 24 27 0 15 May 2023
Visual Anomaly Detection via Dual-Attention Transformer and Discriminative Flow Haiming Yao Wei Luo Wenyong Yu ViT 26 3 0 31 Mar 2023
Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection Haiming Yao Wenyong Yu Wei Luo Zhenfeng Qiang Donghao Luo Xiaotian Zhang 21 21 0 10 Mar 2023
Anomaly Detection Requires Better Representations Tal Reiss Niv Cohen Eliahu Horwitz Ron Abutbul Yedid Hoshen OOD AI4TS SSL 44 21 0 19 Oct 2022