From the 1 of 7 linked papers with an AI index.
7 papers
: Reactive Real-time Flow Policies
Sungjae Park, Shubham Tulsiani
The paper introduces πR², a method that makes large pretrained manipulation policies reactive and real-time by separating fast proprioceptive inputs from slower vision-language inp…
DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policy
Sungjae Park, Homanga Bharadhwaj, Shubham Tulsiani
We propose DemoDiffusion, a simple method for enabling robots to perform manipulation tasks by imitating a single human demonstration, without requiring task-specific training or p…
Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models
Yanbo Xu, Yu Wu, Sungjae Park +2
We present a mechanism to steer the sampling diversity of denoising diffusion and flow matching models, allowing users to sample from a sharper or broader distribution than the tra…
Dex4D: Task-Agnostic Point Track Policy for Sim-to-Real Dexterous Manipulation
Yuxuan Kuang, Sungjae Park, Katerina Fragkiadaki +1
Learning generalist policies capable of accomplishing a plethora of everyday tasks remains an open challenge in dexterous manipulation. In particular, collecting large-scale manipu…
BG-HOP: A Bimanual Generative Hand-Object Prior
Sriram Krishna, Sravan Chittupalli, Sungjae Park
In this work, we present BG-HOP, a generative prior that seeks to model bimanual hand-object interactions in 3D. We address the challenge of limited bimanual interaction data by ex…
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair +98
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…