AI2-THOR

AI2-THOR: An Interactive 3D Environment for Visual AI. We introduce The House Of inteRactions (THOR), a framework for visual AI research, available at this http URL. 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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References in zbMATH (referenced in 1 article )

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  1. Kwanyoung Park, Hyunseok Oh, Youngki Lee: VECA : A Toolkit for Building Virtual Environments to Train and Test Human-like Agents (2021) arXiv


Further publications can be found at: https://ai2thor.allenai.org/publications