Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection

6 August 2023

Papers citing "Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection"

9 / 9 papers shown

Title
AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection Bin-Bin Gao Yue Zhu Jiangtao Yan Y. Cai Wenbo Zhang Meng Wang Jun Liu Yong-Jin Liu L. Wang Chengjie Wang VLM 41 0 0 15 May 2025
Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt Bin-Bin Gao 34 4 0 14 May 2025
MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning Bin-Bin Gao VLM 25 0 0 14 May 2025
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection Yuanze Li Haolin Wang Shihao Yuan Ming-Yu Liu Debin Zhao Yiwen Guo Chen Xu Guangming Shi Wangmeng Zuo 83 29 0 20 Jan 2025
Anomaly Detection via Reverse Distillation from One-Class Embedding Hanqiu Deng Xingyu Li UQCV 117 448 0 26 Jan 2022
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection Marco Rudolph Tom Wehrbein Bodo Rosenhahn Bastian Wandt UQCV 78 208 0 06 Oct 2021
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
Inpainting Transformer for Anomaly Detection Jonathan Pirnay K. Chai ViT 107 165 0 28 Apr 2021
DFR: Deep Feature Reconstruction for Unsupervised Anomaly Segmentation Jie Yang Yong Shi Zhiquan Qi UQCV 109 115 0 13 Dec 2020