3D-BSLS-6D

Dataset consist of both real captures from Photoneo PhoXi structured light scanner devices annotated by hand and synthetic samples produced by custom generator. In comparison with existing datasets for 6D pose estimation, some notable differences include:

• most of the captured bins are texture-less, made from uniform, single-colored materials,
• all bins are of cuboid shape with different proportions. Compared to objects with complex geometry, bins consist of flat faces with edges, which are not guaranteed to be seen in the capture due to occlusion. Surface models of these bins are not provided, just their approximate bounding boxes,
• PhoXi scanner provides high-resolution 3D geometry data, but no RGB data, with a rough and noisy gray-scale intensity image being the closest equivalent,
• captures come from different devices with various intrinsic camera parameters. 3D point clouds contain these parameters implicitly as opposed to RGBD images.

Due to its currently limited size, we recommend cross-validation instead of an explicit train-validation split. We plan to add more samples into the dataset. NOTE: Annotation files with suffixes _bad, _ish or _catastrophic should be ignored. It was not possible to annotate them correctly with our current toolset.