AI2-THOR: An Interactive 3D Environment for Visual AI
Eric Kolve
Roozbeh Mottaghi
Winson Han
Eli VanderBilt
Luca Weihs
Alvaro Herrasti
Matt Deitke
Kiana Ehsani
Daniel Gordon
Yuke Zhu
Aniruddha Kembhavi
Abhinav Gupta
Ali Farhadi

Abstract
We introduce The House Of inteRactions (THOR), a framework for visual AI research, available at http://ai2thor.allenai.org. AI2-THOR consists of near photo-realistic 3D indoor scenes, where AI agents can navigate in the scenes and interact with objects to perform tasks. AI2-THOR enables research in many different domains including but not limited to deep reinforcement learning, imitation learning, learning by interaction, planning, visual question answering, unsupervised representation learning, object detection and segmentation, and learning models of cognition. The goal of AI2-THOR is to facilitate building visually intelligent models and push the research forward in this domain.
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