Fraunhofer IPA Bin-Picking

Introduced by Kleeberger et al. in Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking

The Fraunhofer IPA Bin-Picking dataset is a large-scale dataset comprising both simulated and real-world scenes for various objects (potentially having symmetries) and is fully annotated with 6D poses. A pyhsics simulation is used to create scenes of many parts in bulk by dropping objects in a random position and orientation above a bin. Additionally, this dataset extends the Siléane dataset by providing more samples. This allows to e.g. train deep neural networks and benchmark the performance on the public Siléane dataset



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