MineDojo Internet Knowledge Base (YouTube)
Creators
- 1. NVIDIA
- 2. Caltech
- 3. Stanford
- 4. Columbia
- 5. SJTU
- 6. NVIDIA, UT Austin
- 7. NVIDIA, Caltech
Description
Project website: minedojo.org
Paper: arxiv.org/abs/2206.08853
GitHub: github.com/MineDojo/MineDojo
Minecraft is among the most streamed games on YouTube. Human players have demonstrated a stunning range of creative activities and sophisticated missions that take hours to complete. We collect 730K+ narrated Minecraft videos, which add up to 33 years of duration and 2.2B words in English transcripts. The time-aligned transcripts enable the agent to ground free-form natural language in video pixels and learn the semantics of diverse activities without laborious human labeling.
There are two files in our YouTube knowledge base.
- youtube_tutorial.json (tutorial videos):
Minecraft tutorial videos include step-by-step demonstrations and sometimes detailed verbal explanations. They also serve as a rich source of creative missions that humans find interesting. We harvest thousands of tasks from these videos in our benchmarking suite.
- youtube_full.json (general gameplay videos):
Unlike tutorials, general gameplay videos do not necessarily provide guidance on particular tasks. Instead, they capture the “in-the-wild” human experiences that are much larger in quantity, diverse in contents, and rich in learning signals.
Data Structure
list[
{
"id": str, # video id
"title": str, # video title
"link": str, # video link
"view_count": int # number of times the video has been viewed
"like_count": int # number of users who have indicated that they liked the video
"duration": float # video duration in seconds
"fps": float, # video FPS
}
]
Check out our paper!
@article{fan2022minedojo,
title = {MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge},
author = {Linxi Fan and Guanzhi Wang and Yunfan Jiang and Ajay Mandlekar and Yuncong Yang and Haoyi Zhu and Andrew Tang and De-An Huang and Yuke Zhu and Anima Anandkumar},
year = {2022},
journal = {arXiv preprint arXiv: Arxiv-2206.08853}
}