VirtualHome: Simulating Household Activities Via Programs
Name
1806.07011.pdf
Description
Accepted version
Size
6.58 MB
Format
Adobe PDF
Checksum (MD5)
8c13374c94c5e0af846775694bdd0d19
Author(s)
Puig, Xavier
Ra, Kevin
Boben, Marko
Li, Jiaman
Wang, Tingwu
Fidler, Sanja
Torralba, Antonio
Date Issued
December 2018
Journal
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Publisher
IEEE
Citation
Puig, Xavier, et al. "VirtualHome: Simulating Household Activities Via Programs." IEEE/CVF Conference on Computer Vision and Pattern Recognition (June 2018): 18326092 © 2018 Author(s)
Version
Author's final manuscript
Abstract
In this paper, we are interested in modeling complex activities that occur in a typical household. We propose to use programs, i.e., sequences of atomic actions and interactions, as a high level representation of complex tasks. Programs are interesting because they provide a non-ambiguous representation of a task, and allow agents to execute them. However, nowadays, there is no database providing this type of information. Towards this goal, we first crowd-source programs for a variety of activities that happen in people's homes, via a game-like interface used for teaching kids how to code. Using the collected dataset, we show how we can learn to extract programs directly from natural language descriptions or from videos. We then implement the most common atomic (inter)actions in the Unity3D game engine, and use our programs to 'drive' an artificial agent to execute tasks in a simulated household environment. Our VirtualHome simulator allows us to create a large activity video dataset with rich ground-truth, enabling training and testing of video understanding models. We further showcase examples of our agent performing tasks in our VirtualHome based on language descriptions. © 2018 IEEE.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CVPR.2018.00886
