The MVTec 3D Anomaly Detection Dataset (MVTec 3D-AD)

MVTec 3D Anomaly Detection Dataset (MVTec 3D-AD) is a comprehensive 3D dataset for the task of unsupervised anomaly detection and localization. It contains over 4000 high-resolution scans acquired by an industrial 3D sensor. Each of the 10 different object categories comprises a set of defect-free training and validation samples and a test set of samples with various kinds of defects. Precise ground-truth annotations are provided for each anomalous test sample.

More information can be found in our corresponding paper titled "The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization". This work was awarded the Best Industrial Paper Award at the 17th International Conference on Computer Vision Theory and Applications (VISAPP / VISIGRAPP).

PLEASE NOTE: LICENSE TERMS & ATTRIBUTION

The data is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). In particular, it is not allowed to use the dataset for commercial purposes. If you are unsure whether or not your application violates the non-commercial use clause of the license, please contact us via the form below.

If you use this dataset in scientific work, please cite our paper:

Paul Bergmann, Xin Jin, David Sattlegger, Carsten Steger: The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization;
 in: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, 202-213, 2022, DOI: 10.5220/0010865000003124.

Download the MVTec 3D-AD Dataset

We provide a download link for the whole dataset, as well as links for each object category. For each object, the data consists of four folders:

  • 'train', which contains the defect-free training samples.
  • 'validation', which contains the defect-free validation samples.
  • 'test', which contains the defective and defect-free test samples.
  • 'calibration', which contains the internal camera parameters of the 3D sensor.

Each dataset split contains two subdirectories:

  • 'xyz', which contains 3-channel TIFF images that store the x,y, and z coordinates.
  • 'rgb', which contains 3-channel PNG images that store the corresponding RGB values for each 3D point.

The test split additionally includes a ground truth directory 'gt'. For each test sample, this directory contains a 1-channel PNG image. It indicates, for each image pixel, whether a defect is present or not. The defect type is reflected in the pixel value of the image. The mapping between defect names and pixel values is specified in the file class_ids.json.

Download the whole dataset

Since the whole dataset is about 13.2 GB in size, we also provide links to download each object category separately:

Evaluation Code

In order to ensure a fair and consistent comparison of new and existing methods on our dataset, we provide python scripts that allow an easy evaluation. For details on how to use the script, please have a look at the included readme file.

Download the evaluation code

Contact Form MVTec 3D-AD

Contact Form MVTec 3D-AD
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