384 citations · 4.5k across the 97 of their papers we have counts for
122 papers
Self-Activating Neural Ensembles for Continual Reinforcement Learning
Sam Powers, Eliot Xing, Abhinav Gupta
The ability for an agent to continuously learn new skills without catastrophically forgetting existing knowledge is of critical importance for the development of generally intellig…
Learning State-Aware Visual Representations from Audible Interactions
Himangi Mittal, Pedro Morgado, Unnat Jain +1
We propose a self-supervised algorithm to learn representations from egocentric video data. Recently, significant efforts have been made to capture humans interacting with their ow…
What's in your hands? 3D Reconstruction of Generic Objects in Hands
Yufei Ye, Abhinav Gupta, Shubham Tulsiani
Our work aims to reconstruct hand-held objects given a single RGB image. In contrast to prior works that typically assume known 3D templates and reduce the problem to 3D pose estim…
Pre-train, Self-train, Distill: A simple recipe for Supersizing 3D Reconstruction
Kalyan Vasudev Alwala, Abhinav Gupta, Shubham Tulsiani
Our work learns a unified model for single-view 3D reconstruction of objects from hundreds of semantic categories. As a scalable alternative to direct 3D supervision, our work reli…
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control
Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam +1
Recent years have seen the emergence of pre-trained representations as a powerful abstraction for AI applications in computer vision, natural language, and speech. However, policy…
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
Simone Parisi, Victoria Dean, Deepak Pathak +1
Common approaches for task-agnostic exploration learn tabula-rasa --the agent assumes isolated environments and no prior knowledge or experience. However, in the real world, agents…