44 citations · 46 across the 3 of their papers we have counts for
5 papers
A General Purpose Supervisory Signal for Embodied Agents
Kunal Pratap Singh, Jordi Salvador, Luca Weihs +1
Training effective embodied AI agents often involves manual reward engineering, expert imitation, specialized components such as maps, or leveraging additional sensors for depth an…
ASC me to Do Anything: Multi-task Training for Embodied AI
Jiasen Lu, Jordi Salvador, Roozbeh Mottaghi +1
Embodied AI has seen steady progress across a diverse set of independent tasks. While these varied tasks have different end goals, the basic skills required to complete them succes…
AllenAct: A Framework for Embodied AI Research
Luca Weihs, Jordi Salvador, Klemen Kotar +4
The domain of Embodied AI, in which agents learn to complete tasks through interaction with their environment from egocentric observations, has experienced substantial growth with…
Learning About Objects by Learning to Interact with Them
Martin Lohmann, Jordi Salvador, Aniruddha Kembhavi +1
Much of the remarkable progress in computer vision has been focused around fully supervised learning mechanisms relying on highly curated datasets for a variety of tasks. In contra…
RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
Matt Deitke, Winson Han, Alvaro Herrasti +10
Visual recognition ecosystems (e.g. ImageNet, Pascal, COCO) have undeniably played a prevailing role in the evolution of modern computer vision. We argue that interactive and embod…