Action Learning From Realistic Environments and Directives (ALFRED)
Multi-Modal LearningEnglish
Created by Shridhar et al. at 2020, the Action Learning From Realistic Environments and Directives (ALFRED) is a multi-modal learning dataset in English containing 8,055 records in JSON format.
About Action Learning From Realistic Environments and Directives (ALFRED)
Dataset contains 8k+ expert demostrations with 3 or more language annotations each comprising of 25,000 language directives. A trajectory consists of a sequence of expert actions, the corresponding image observations, and language annotations describing segments of the trajectory.
Details
- Task
- Multi-Modal Learning
- Language
- English
- Format
- JSON
- Rows / instances
- 8,055
- Creator
- Shridhar et al.
- Year
- 2020