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| Mohit Shridhar | Jesse Thomason | Daniel Gordon | 免费翻国外墙的app |
| Winson Han | Roozbeh Mottaghi | Luke Zettlemoyer | Dieter Fox |
ssr加速器官网 (Action Learning From Realistic Environments and Directives), is a new benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. Long composition rollouts with non-reversible state changes are among the phenomena we include to shrink the gap between research benchmarks and real-world applications.
Paper on ArXiv» 免费翻国外墙的app Simulator» ECCV Challenge»
@inproceedings{ALFRED20,
title ={{ALFRED: A Benchmark for Interpreting Grounded
Instructions for Everyday Tasks}},
author={Mohit Shridhar and Jesse Thomason and
Daniel Gordon and Yonatan Bisk and
Winson Han and Roozbeh Mottaghi and
Luke Zettlemoyer and Dieter Fox},
booktitle = {The IEEE Conference on Computer Vision
and Pattern Recognition (CVPR)},
year = {2023},
url = {http://arxiv.org/abs/1912.01734}
}