312 citations · 537 across the 37 of their papers we have counts for
6 papers · 1 filter
Towards Disturbance-Free Visual Mobile Manipulation
Tianwei Ni, Kiana Ehsani, Luca Weihs +1
Deep reinforcement learning has shown promising results on an abundance of robotic tasks in simulation, including visual navigation and manipulation. Prior work generally aims to b…
Simple but Effective: CLIP Embeddings for Embodied AI
Apoorv Khandelwal, Luca Weihs, Roozbeh Mottaghi +1
Contrastive language image pretraining (CLIP) encoders have been shown to be beneficial for a range of visual tasks from classification and detection to captioning and image manipu…
Pushing it out of the Way: Interactive Visual Navigation
Kuo-Hao Zeng, Luca Weihs, Ali Farhadi +1
We have observed significant progress in visual navigation for embodied agents. A common assumption in studying visual navigation is that the environments are static; this is a lim…
GridToPix: Training Embodied Agents with Minimal Supervision
Unnat Jain, Iou-Jen Liu, Svetlana Lazebnik +3
While deep reinforcement learning (RL) promises freedom from hand-labeled data, great successes, especially for Embodied AI, require significant work to create supervision via care…
ManipulaTHOR: A Framework for Visual Object Manipulation
Kiana Ehsani, Winson Han, Alvaro Herrasti +5
The domain of Embodied AI has recently witnessed substantial progress, particularly in navigating agents within their environments. These early successes have laid the building blo…
Visual Room Rearrangement
Luca Weihs, Matt Deitke, Aniruddha Kembhavi +1
There has been a significant recent progress in the field of Embodied AI with researchers developing models and algorithms enabling embodied agents to navigate and interact within…