ego4d-video

EgoCOT is a large-scale embodied planning dataset, which selected egocentric videos from the Ego4D dataset and corresponding high-quality step-by-step language instructions, which are machine generated, then semantics-based filtered, and finally human-verified. For mored details, please visit [EgoCOT_Dataset](https://github.com/EmbodiedGPT/EgoCOT_Dataset/blob/main/README.md). If you find this dataset useful, please consider citing the paper, ```bibtex @article{mu2024embodiedgpt, title={Embodiedgpt: Vision-language pre-training via embodied chain of thought}, author={Mu, Yao and Zhang, Qinglong and Hu, Mengkang and Wang, Wenhai and Ding, Mingyu and Jin, Jun and Wang, Bin and Dai, Jifeng and Qiao, Yu and Luo, Ping}, journal={Advances in Neural Information Processing Systems}, volume={36}, year={2024} } ```EgoCOT是一款大规模具身规划数据集，其从Ego4D数据集中选取自我中心视角视频，并配备对应的高质量分步语言指令。该类指令先由机器生成，再经基于语义的筛选，最终通过人工核验。 如需了解更多详情，请访问[EgoCOT_Dataset](https://github.com/EmbodiedGPT/EgoCOT_Dataset/blob/main/README.md)。 若本数据集对您的研究有所助益，请考虑引用以下论文： bibtex @article{mu2024embodiedgpt, title={EmbodiedGPT: 基于具身思维链的视觉语言预训练}, author={穆尧、张庆龙、胡孟康、王文海、丁明宇、金俊、王斌、戴吉锋、乔宇、罗平}, journal={《神经信息处理系统进展》}, volume={36}, year={2024} }

搜集汇总

背景与挑战

背景概述

该数据集为EgoCOT，是一个大规模具身规划数据集，基于Ego4D的第一人称视频构建，提供了机器生成并经语义过滤和人工验证的逐步语言指令。数据集主要用于支持具身思维链的视觉语言预训练研究。