MPI stands for Moldflow Plastic Insight, which is a dataset consisting of more than 1 million images of physical 3D objects. The images have seven variation factors, such as the color, shape, size, and position of the objects. This dataset can be used to test representation learning algorithms in simulated and real environments. The dataset has four subsets: Real world simple shapes (mpi3d_real), Realistic rendered images (mpi3d_realistic), Simplistic rendered images (mpi3d_toy), and Complex real world shapes (mpi3d_complex), the first three containing 1,036,800 images and the last containing 460,800 images.

Citation

@inproceedings{NEURIPS2019_d97d404b, author = {Gondal, Muhammad Waleed and Wuthrich, Manuel and Miladinovic, Djordje and Locatello, Francesco and Breidt, Martin and Volchkov, Valentin and Akpo, Joel and Bachem, Olivier and Sch"{o}lkopf, Bernhard and Bauer, Stefan}, booktitle = {Advances in Neural Information Processing Systems}, editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch'{e}-Buc and E. Fox and R. Garnett}, pages = {}, publisher = {Curran Associates, Inc.}, title = {On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset}, url = {https://proceedings.neurips.cc/paper/2019/file/d97d404b6119214e4a7018391195240a-Paper.pdf}, volume = {32}, year = {2019} }