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In this paper, we introduce a new public dataset for 6D object poseestimation and instance segmentation for industrial bin-picking. The datasetcomprises both synthetic and real-world scenes. For both, point clouds, depthimages, and annotations comprising the 6D pose (position and orientation), avisibility score, and a segmentation mask for each object are provided. Alongwith the raw data, a method for precisely annotating real-world scenes isproposed. To the best of our knowledge, this is the first public dataset for 6Dobject pose estimation and instance segmentation for bin-picking containingsufficiently annotated data for learning-based approaches. Furthermore, it isone of the largest public datasets for object pose estimation in general. Thedataset is publicly available at http://www.bin-picking.ai/en/dataset.html.

Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking