Embodied Question Answering

Code

• github.com/facebookresearch/House3D
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• github.com/facebookresearch/EmbodiedQA
  pytorch★ 0
• github.com/abhshkdz/House3D
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• github.com/jxwuyi/House3D
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Abstract

We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the car?"). In order to answer, the agent must first intelligently navigate to explore the environment, gather information through first-person (egocentric) vision, and then answer the question ("orange"). This challenging task requires a range of AI skills -- active perception, language understanding, goal-driven navigation, commonsense reasoning, and grounding of language into actions. In this work, we develop the environments, end-to-end-trained reinforcement learning agents, and evaluation protocols for EmbodiedQA.

Tasks

Reproductions