The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization

16 Dec 2021  ·  Paul Bergmann, Xin Jin, David Sattlegger, Carsten Steger ·

We introduce the first comprehensive 3D dataset for the task of unsupervised anomaly detection and localization. It is inspired by real-world visual inspection scenarios in which a model has to detect various types of defects on manufactured products, even if it is trained only on anomaly-free data. There are defects that manifest themselves as anomalies in the geometric structure of an object. These cause significant deviations in a 3D representation of the data. We employed a high-resolution industrial 3D sensor to acquire depth scans of 10 different object categories. For all object categories, we present a training and validation set, each of which solely consists of scans of anomaly-free samples. The corresponding test sets contain samples showing various defects such as scratches, dents, holes, contaminations, or deformations. Precise ground-truth annotations are provided for every anomalous test sample. An initial benchmark of 3D anomaly detection methods on our dataset indicates a considerable room for improvement.

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Datasets


Introduced in the Paper:

MVTEC 3D-AD
Task Dataset Model Metric Name Metric Value Global Rank Benchmark
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel VM Segmentation AUPRO 0.471 # 7
Detection AUCROC 0.609 # 6
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel GAN Segmentation AUPRO 0.583 # 7
Detection AUROC 0.537 # 8
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel GAN Segmentation AUPRO 0.639 # 5
Detection AUCROC 0.517 # 8
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel AE Segmentation AUPRO 0.564 # 6
Detection AUCROC 0.538 # 7
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth VM Segmentation AUPRO 0.374 # 10
Detection AUROC 0.546 # 10
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth AE Segmentation AUPRO 0.203 # 11
Detection AUROC 0.546 # 10
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth GAN Segmentation AUPRO 0.143 # 12
Detection AUROC 0.523 # 12
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel VM Segmentation AUPRO 0.492 # 8
Detection AUROC 0.571 # 7
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel AE Segmentation AUPRO 0.348 # 9
Detection AUROC 0.699 # 6

Methods


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