AI2-THOR: An Interactive 3D Environment for Visual AI
Eric Kolve1, Roozbeh Mottaghi1,2, Winson Han1, Eli VanderBilt1, Luca Weihs1, Alvaro Herrasti1, Matt Deitke1,2, Kiana Ehsani1, Daniel Gordon2, Yuke Zhu3, Aniruddha Kembhavi1,2, Abhinav Gupta1,4, Ali Farhadi1,2 1Allen Institute for AI, 2University of Washington, 3Stanford University, 4Carnegie Mellon University Figure 1: AI2-THOR consists of interactive 3D environments that can be used with embodied agents.
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.
原文 arXiv:1712.05474;中英对照 + 大白话阅读 https://aha.fim.ai/paper/1712.05474v4