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Lars Heckler
Lars Heckler
PhD Student, MVTec Software GmbH & Technical University of Munich (TUM)
Verified email at mvtec.com
Title
Cited by
Cited by
Year
Efficientad: Accurate visual anomaly detection at millisecond-level latencies
K Batzner, L Heckler, R König
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
1522024
Exploring the importance of pretrained feature extractors for unsupervised anomaly detection and localization
L Heckler, R König, P Bergmann
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
202023
Registration strategy of point clouds based on region-specific projections and virtual structures for robot-based inspection systems
P Bauer, L Heckler, M Worack, A Magańa, G Reinhart
Measurement 185, 109963, 2021
122021
Feature Selection for Unsupervised Anomaly Detection and Localization Using Synthetic Defects
L Heckler, R König
Proceedings Copyright 154, 165, 2024
12024
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies Supplementary Material
K Batzner, L Heckler, R König
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Articles 1–5