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AI2-THOR: An Interactive 3D Environment for Visual AI

Authors :
Kolve, Eric
Mottaghi, Roozbeh
Han, Winson
VanderBilt, Eli
Weihs, Luca
Herrasti, Alvaro
Deitke, Matt
Ehsani, Kiana
Gordon, Daniel
Zhu, Yuke
Kembhavi, Aniruddha
Gupta, Abhinav
Farhadi, Ali
Publication Year :
2017

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1712.05474
Document Type :
Working Paper