OpenGVLab/InternVid-Full

我们介绍了InternVid-230M，这是该数据集的完整版本，包含2.3亿个视频剪辑，这些剪辑来自公开的网络视频，并附有生成的高质量字幕。We introduce InternVid-230M, the full version of this dataset, which contains 230 million video clips sourced from publicly available web videos and paired with high-quality generated captions.

原始信息汇总

InternVid 数据集概述

数据集描述

• 主页: InternVid
• 仓库: OpenGVLab
• 论文: 2307.06942
• 联系人: mailto:InternVideo

InternVid-Full

InternVid-230M 是一个完整的数据集，包含 2.3 亿个视频片段，为公开可用的网络视频生成高质量的描述。

下载

2.3 亿个样本以 jsonlines 文件格式提供。列包括视频ID、时间戳、生成的描述及其 UMT 相似度分数。

使用方法

python from datasets import load_dataset dataset = load_dataset("OpenGVLab/InternVid-Full")

方法

引用

如果您发现此工作对您的研究有用，请考虑引用 InternVid。您的认可将极大地帮助我们继续为研究社区贡献资源。

bibtex @article{wang2023internvid, title={InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation}, author={Wang, Yi and He, Yinan and Li, Yizhuo and Li, Kunchang and Yu, Jiashuo and Ma, Xin and Chen, Xinyuan and Wang, Yaohui and Luo, Ping and Liu, Ziwei and Wang, Yali and Wang, Limin and Qiao, Yu}, journal={arXiv preprint arXiv:2307.06942}, year={2023} } @article{wang2022internvideo, title={InternVideo: General Video Foundation Models via Generative and Discriminative Learning}, author={Wang, Yi and Li, Kunchang and Li, Yizhuo and He, Yinan and Huang, Bingkun and Zhao, Zhiyu and Zhang, Hongjie and Xu, Jilan and Liu, Yi and Wang, Zun and Xing, Sen and Chen, Guo and Pan, Junting and Yu, Jiashuo and Wang, Yali and Wang, Limin and Qiao, Yu}, journal={arXiv preprint arXiv:2212.03191}, year={2022} }