Abstract: With the rapid advancement of generative models, their potential to transform creative content creation is increasingly evident. However, most large-scale generative models are primarily text-conditioned, given the availability of large-scale paired text–image datasets. In contrast, for most practical applications, creators often begin from an existing asset and wish to generate variations or modify it in [...]

Abstract: Tool manipulation is an essential human skill. It expands our manipulation capability beyond the capability of the biological hand, and is a defining feature of many tasks centered on physical interaction with the real world. For humanoid robots to become general-purpose, they must master tool manipulation as well. However, the state-of-the-art humanoid robots equipped with [...]

Abstract: A core challenge in vision is building representations that capture 3D scenes over time for perception and interactive generation. For accurate perception and plausible generation, we want consistency across views, time, and modalities. In this talk we explore consistency through the choice of representation, moving from dense grid formulations to entity-centric scenes that are easier to [...]

Abstract: Advances in visual imitation learning driven by large-scale data and expressive policy architectures have yielded impressive progress on long-horizon, dexterous tasks. However, current success rates remain insufficient for industrial deployment, which demands near-perfect reliability on novel tasks. Compared to other fields such as NLP and CV, the available data in robotics is several orders [...]