Search papers, labs, and topics across Lattice.
Affiliation:
6
0
4
0
A single set of learned manipulation skills transfers to the real world with 78% success, bypassing the need for task-specific fine-tuning or re-training on real data.
An automated pipeline that converts hair-card models into high-quality strand-based hairstyles that preserves the original hairstyle while enriching it with fine-scale geometric detail and adhering to standard production requirements is presented.
Kuafu's ability to synthesize robust policies from language and task semantics achieves over 82% success in complex manipulation tasks, revolutionizing how we approach control-to-learning paradigms.
RoboEdit transforms abundant human manipulation videos into high-fidelity training data for robots, unlocking new avenues for scalable robot learning.
Cloning synthetic demonstrations alone caps performance, but combining it with reinforcement learning unlocks superior real-world manipulation capabilities.
