Fractals as Pre-training Datasets for Anomaly Detection and Localization

11 May 2024

Papers citing "Fractals as Pre-training Datasets for Anomaly Detection and Localization"

11 / 11 papers shown

Title
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization Sungwook Lee Seunghyun Lee B. Song 70 190 0 09 Jun 2022
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows Jiawei Yu1 Ye Zheng Xiang Wang Wei Li Yushuang Wu Rui Zhao Liwei Wu 51 309 0 15 Nov 2021
Improving Fractal Pre-training Connor Anderson Ryan Farrell 104 27 0 06 Oct 2021
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows Denis A. Gudovskiy Shun Ishizaka Kazuki Kozuka 80 400 0 27 Jul 2021
Towards Total Recall in Industrial Anomaly Detection Karsten Roth Latha Pemula J. Zepeda Bernhard Schölkopf Thomas Brox Peter V. Gehler UQCV 76 901 0 15 Jun 2021
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization Thomas Defard Aleksandr Setkov Angélique Loesch Romaric Audigier UQCV 67 827 0 17 Nov 2020
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation Tal Reiss Niv Cohen Liron Bergman Yedid Hoshen 54 249 0 12 Oct 2020
What is being transferred in transfer learning? Behnam Neyshabur Hanie Sedghi Chiyuan Zhang 76 513 0 26 Aug 2020
Scaling Out-of-Distribution Detection for Real-World Settings Dan Hendrycks Steven Basart Mantas Mazeika Andy Zou Joe Kwon Mohammadreza Mostajabi Jacob Steinhardt D. Song OODD 126 465 0 25 Nov 2019
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings Paul Bergmann Michael Fauser David Sattlegger C. Steger 66 660 0 06 Nov 2019
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 135 2,386 0 10 Jul 2017