Introducing MVTec ITODD - A Dataset for 3D Object Recognition in Industry

Bertram Drost, Markus Ulrich, Paul Bergmann, Philipp Hartinger, Carsten Steger; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 2200-2208

We introduce the MVTec Industrial 3D Object Detection Dataset (MVTec ITODD), a public dataset for 3D object detection and pose estimation with a strong focus on ob- jects, settings, and requirements that are realistic for indus- trial setups. Contrary to other 3D object detection datasets that often represent scenarios from everyday life or mo- bile robotic environments, our setup models industrial bin picking and object inspection tasks that often face different challenges. Additionally, the evaluation citeria are focused on practical aspects, such as runtimes, memory consump- tion, useful correctness measurements, and accuracy. The dataset contains 28 objects with different characteristics, arranged in over 800 scenes and labeled with around 3500 rigid 3D transformations of the object instances as ground truth.