SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation

28 July 2022

Papers citing "SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation"

7 / 57 papers shown

Title
$FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation$ FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation X. Xia Weijie Lv Xing He Nan Li Chuanqi Liu Ning Ding 35 1 0 30 Jan 2023
FRE: A Fast Method For Anomaly Detection And Segmentation I. Ndiour Nilesh A. Ahuja Ergin Utku Genc Omesh Tickoo 48 2 0 23 Nov 2022
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detection Tongkun Liu Bing Li Zhu Zhao Xiaoyu Du Bin Jiang Leqi Geng 28 35 0 26 Oct 2022
Anomaly Detection via Reverse Distillation from One-Class Embedding Hanqiu Deng Xingyu Li UQCV 114 448 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
Instance Localization for Self-supervised Detection Pretraining Ceyuan Yang Zhirong Wu Bolei Zhou Stephen Lin ViT SSL 100 145 0 16 Feb 2021
On the surprising similarities between supervised and self-supervised models Robert Geirhos Kantharaju Narayanappa Benjamin Mitzkus Matthias Bethge Felix Wichmann Wieland Brendel OOD SSL DRL 74 46 0 16 Oct 2020