Having diverse, high-quality 3D assets at scale dramatically improves robot learning in simulation—this dataset removes a major bottleneck for scaling robotic manipulation training.
ManiTwin is an automated pipeline that converts single images into simulation-ready 3D digital objects for robot training. The team created ManiTwin-100K, a dataset of 100,000 annotated 3D assets with physical properties and manipulation instructions, enabling large-scale generation of robot training data in simulation.