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GTC 2018 Silicon Valley

S8582 - Embodied Question Answering

Session Speakers
Session Description

Building intelligent agents that possess the ability to perceive the rich visual environment around us, communicate this understanding in natural language to humans and other agents, and execute actions in a physical environment, has been a long-term goal of Artificial Intelligence. In this talk, I will present my recent work on an instantiation of this goal -- Embodied Question Answering (EQA) -- where an agent that is spawned at a random location in an environment (a house or building) is asked a natural language question ("What color is the car?"). The agent perceives its environment through first-person vision and can perform a few 'atomic' actions: move-{forward, backward, right, left}, and turn-{right, left}. The objective of the agent is to explore the environment and gather visual information necessary to answer the question ("orange"). I'll introduce our OpenGL-based environments, a large-scale dataset of expert demonstrations for this task and deep models, trained end-to-end using reinforcement learning, from raw pixels to multi-step navigation control to visual question answering.


Additional Information
AI/DL Research, Computer Vision
General
Intermediate technical
Talk
25 minutes
Session Schedule