4 papers
SynthICL: Scalable In-context Imitation Learning with Synthetic Data
Cheng Qian, Ruomeng Fan, Yifei Ren +2
In-context imitation learning (ICIL) enables robots to learn new tasks from a small number of demonstrations by conditioning a pre-trained policy on task-specific examples, without…
HoloMotion-1 Technical Report
Maiyue Chen, Kaihui Wang, Bo Zhang +7
In this report, we present HoloMotion-1, a humanoid motion foundation model for zero-shot whole-body motion tracking. A key innovation of HoloMotion-1 is to scale control-policy tr…
Learning in ImaginationLand: Omnidirectional Policies through 3D Generative Models (OP-Gen)
Yifei Ren, Edward Johns
Recent 3D generative models, which are capable of generating full object shapes from just a few images, now open up new opportunities in robotics. In this work, we show that 3D gen…
Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models
Ivan Kapelyukh, Yifei Ren, Ignacio Alzugaray +1
We introduce Dream2Real, a robotics framework which integrates vision-language models (VLMs) trained on 2D data into a 3D object rearrangement pipeline. This is achieved by the rob…