AI2-THOR: An Interactive 3D Environment for Visual AI
December 14, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
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
arXiv ID
1712.05474
Category
cs.CV: Computer Vision
Cross-listed
cs.AI,
cs.LG
Citations
1.3K
Venue
arXiv.org
Last Checked
3 months ago
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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