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

16 Dec 2021arXiv:2112.09045archive 2025-07-28

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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Code

JerryX1110/Awesome-3D-Anomaly-Detection mentioned on GitHubMIT report
openvinotoolkit/anomalib pytorchApache-2.0 report

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Tasks

3D Anomaly Detection and SegmentationAnomaly DetectionDepth Anomaly Detection and SegmentationObjectRGB+3D Anomaly Detection and SegmentationRGB+Depth Anomaly Detection and SegmentationUnsupervised Anomaly Detection

Datasets

Introduced by this paper, per the archive.

MVTEC 3D-AD

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel AE Detection AUROC 0.699 #8 of 11 Archive leaderboard report
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel VM Detection AUROC 0.571 #9 of 11 Archive leaderboard report
3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel GAN Detection AUROC 0.537 #10 of 11 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth VM Detection AUROC 0.546 #11 of 13 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth VM Segmentation AUPRO 0.374 #11 of 13 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth AE Detection AUROC 0.546 #12 of 13 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth AE Segmentation AUPRO 0.203 #12 of 13 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth GAN Detection AUROC 0.523 #13 of 13 Archive leaderboard report
Depth Anomaly Detection and Segmentation MVTEC 3D-AD Depth GAN Segmentation AUPRO 0.143 #13 of 13 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel VM Detection AUCROC 0.609 #7 of 9 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel VM Segmentation AUPRO 0.471 #7 of 9 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel AE Detection AUCROC 0.538 #8 of 9 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel AE Segmentation AUPRO 0.564 #8 of 9 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel GAN Detection AUCROC 0.517 #9 of 9 Archive leaderboard report
RGB+3D Anomaly Detection and Segmentation MVTEC 3D-AD Voxel GAN Segmentation AUPRO 0.639 #9 of 9 Archive leaderboard report

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