65 citations · 145 across the 21 of their papers we have counts for
8 papers · 1 filter
A Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson +2
We discuss some consistent issues on how RepNet has been evaluated in various papers. As a way to mitigate these issues, we report RepNet performance results on different datasets,…
Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation
Homanga Bharadhwaj, Debidatta Dwibedi, Abhinav Gupta +7
How can robot manipulation policies generalize to novel tasks involving unseen object types and new motions? In this paper, we provide a solution in terms of predicting motion info…
OVR: A Dataset for Open Vocabulary Temporal Repetition Counting in Videos
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson +1
We introduce a dataset of annotations of temporal repetitions in videos. The dataset, OVR (pronounced as over), contains annotations for over 72K videos, with each annotation speci…
ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation
ALOHA 2 Team, Jorge Aldaco, Travis Armstrong +23
Diverse demonstration datasets have powered significant advances in robot learning, but the dexterity and scale of such data can be limited by the hardware cost, the hardware robus…
Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers
Vidhi Jain, Maria Attarian, Nikhil J Joshi +10
Large-scale multi-task robotic manipulation systems often rely on text to specify the task. In this work, we explore whether a robot can learn by observing humans. To do so, the ro…
FlexCap: Describe Anything in Images in Controllable Detail
Debidatta Dwibedi, Vidhi Jain, Jonathan Tompson +2
We introduce FlexCap, a vision-language model that generates region-specific descriptions of varying lengths. FlexCap is trained to produce length-conditioned captions for input bo…
RT-H: Action Hierarchies Using Language
Suneel Belkhale, Tianli Ding, Ted Xiao +6
Language provides a way to break down complex concepts into digestible pieces. Recent works in robot imitation learning use language-conditioned policies that predict actions given…
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
Michael Ahn, Debidatta Dwibedi, Chelsea Finn +24
Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data to reason about useful tasks. However,…