add sources for patchcore and efficientaD
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lukas-heiligenbrunner 2024-10-02 18:00:07 +02:00
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@ -22,6 +22,16 @@ Each category comprises a set of defect-free training images and a test set of i
\subsubsection{Few-Shot Learning} \subsubsection{Few-Shot Learning}
\subsubsection{Patchcore}
%todo also show values how they perform on MVTec AD
\subsubsection{EfficientAD}
todo stuff~\cite{patchcorepaper}
% https://arxiv.org/pdf/2106.08265
todo stuff\cite{efficientADpaper}
% https://arxiv.org/pdf/2303.14535
\subsubsection{Jupyter Notebook}\label{subsubsec:jupyternb} \subsubsection{Jupyter Notebook}\label{subsubsec:jupyternb}
A Jupyter notebook is a shareable document which combines code and its output, text and visualizations. A Jupyter notebook is a shareable document which combines code and its output, text and visualizations.

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@ -15,3 +15,23 @@
volume = {14}, volume = {14},
year = {1952} year = {1952}
} }
@misc{efficientADpaper,
title={EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies},
author={Kilian Batzner and Lars Heckler and Rebecca König},
year={2024},
eprint={2303.14535},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2303.14535},
}
@misc{patchcorepaper,
title={Towards Total Recall in Industrial Anomaly Detection},
author={Karsten Roth and Latha Pemula and Joaquin Zepeda and Bernhard Schölkopf and Thomas Brox and Peter Gehler},
year={2022},
eprint={2106.08265},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2106.08265},
}