Datasets For Your Research

MVTec AD is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. It contains over 5,000 high-resolution images divided into fifteen different object and texture categories.

MVTec AD 2 is a dataset for benchmarking unsupervised anomaly detection methods on challenging use-cases from industrial inspection tasks. It expands existing benchmarks by eight new anomaly detection scenarios with more than 8,000 high-resolution images in total. 

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.

The densely segmented supermarket (D2S) dataset is a benchmark for instance-aware semantic segmentation in an industrial domain. It contains 21,000 high-resolution images with pixel-wise labels of all object instances.

The MVTec industrial 3D object detection dataset (MVTec ITODD) is a public dataset for 3D object detection and pose estimation with a strong focus on industrial settings and applications.

The MVTec logical constraints anomaly detection (MVTec LOCO AD) dataset is intended for the evaluation of unsupervised anomaly localization algorithms. The dataset includes both structural and logical anomalies.

The MVTec MV-ball dataset is a publicly available synthetic dataset for evaluating multi-view 6D pose estimation methods. It features a blue sphere with one red and one green hemisphere on its surfaces, which are separated by 90 degrees.

The MVTec Screws dataset has been designed for oriented box detection. It contains 384 images of 13 different types of screws and nuts on a wooden background.

The accuracy of object detectors and trackers is most commonly evaluated by the Intersection over Union (IoU) of the tracker prediction and the ground truth. In all of the common tracking benchmarks, the ground truth is restricted to axis-aligned or oriented boxes.