Youku_Dense_Caption
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# Youku Dense Caption Dataset 🎥 <div align="center">     </div> ## 📊 Dataset Overview A comprehensive collection of Chinese video captions from Youku (优酷), featuring: - **📹 Videos**: 31,466 complete short videos - **✍️ Captions**: 311,921 Chinese captions - **🈺 Language**: Chinese - **📱 Source**: Youku Platform (优酷) ## 🚀 Usage The dataset is available for download from [ModelScope](https://modelscope.cn/datasets/os_ai/Youku_Dense_Caption/). ### 1. Dataset Download ⬇️ ```bash # Install Git LFS git lfs install # Clone the dataset git lfs clone https://oauth2:your_git_token@www.modelscope.cn/datasets/os_ai/Youku_Dense_Caption.git ``` > 🔑 **Get Token**: Visit https://modelscope.cn/my/myaccesstoken ### 2. Dataset Structure 📁 #### 📌 benchmark_files/ Specialized benchmark data collections: - 🎯 Video caption generation task data - 📍 Video moment retrieval task data #### 📌 meta_files/ Core dataset metadata: - 📝 Video category information - 🔗 Video file paths - 💬 Complete caption text #### 📌 data_files/ Main data storage, organized by categories: ``` data_files/ ├── Agriculture/ │ ├── train/ (zipped) │ ├── val/ (zipped) │ └── test/ (ready for preview) ├── Children/ └── ... ``` ### 3. Usage Guide 📖 1. **After Download**: - Navigate to target category folder - Example: `cd data_files/Agriculture` 2. **Data Preparation**: - Unzip files in train/ and val/ directories - Files in test/ directory are ready to use > ⚠️ **Important Notes**: > - train and val data are stored in compressed format, requiring extraction > - test data is directly accessible for preview and testing --- 💡 For questions, please refer to project documentation or submit an Issue ## 📚 Citation If you use this dataset in your research, please cite: ```bibtex @inproceedings{xiong2025youku, title={Youku Dense Caption: A Large-scale Chinese Video Dense Caption Dataset and Benchmarks}, author={Zixuan Xiong, Guangwei Xu, Wenkai Zhang, Yuan Miao, Xuan Wu, LinHai, Ruijie Guo, Hai-Tao Zheng}, booktitle={The Thirteenth International Conference on Learning Representations}, year={2025}, url={https://openreview.net/forum?id=vvi5OjPhbu} } ``` ## 📄 License This dataset is released under the [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. --- <div align="center"> ⭐ Star us on GitHub if you find this dataset useful! ⭐ </div>
# 优酷密集字幕数据集(Youku Dense Caption Dataset) 🎥 <div align="center">     </div> ## 📊 数据集概览 本数据集为来自优酷(Youku)的中文视频字幕综合合集,包含以下内容: - **📹 视频**:31466条完整短视频 - **✍️ 字幕**:311921条中文字幕 - **🈺 语言**:中文 - **📱 来源**:优酷平台 ## 🚀 使用方式 本数据集可从魔搭社区(ModelScope)下载,地址为:[ModelScope](https://modelscope.cn/datasets/os_ai/Youku_Dense_Caption/)。 ### 1. 数据集下载 ⬇️ bash # 安装Git LFS git lfs install # 克隆数据集 git lfs clone https://oauth2:your_git_token@www.modelscope.cn/datasets/os_ai/Youku_Dense_Caption.git > 🔑 **获取访问令牌**:访问 https://modelscope.cn/my/myaccesstoken ### 2. 数据集结构 📁 #### 📌 benchmark_files/ 专业化基准数据集集合: - 🎯 视频字幕生成任务数据集 - 📍 视频时序检索任务数据集 #### 📌 meta_files/ 核心数据集元数据: - 📝 视频分类信息 - 🔗 视频文件路径 - 💬 完整字幕文本 #### 📌 data_files/ 主数据存储目录,按类别组织: data_files/ ├── Agriculture/ │ ├── train/ (已压缩) │ ├── val/ (已压缩) │ └── test/ (可直接预览) ├── Children/ └── ... ### 3. 使用指南 📖 1. **下载完成后**: - 进入目标分类文件夹 - 示例命令:`cd data_files/Agriculture` 2. **数据准备**: - 解压train/与val/目录下的压缩文件 - test/目录下的文件可直接使用 > ⚠️ **重要提示**: > - train与val数据以压缩格式存储,需解压后方可使用 > - test数据可直接用于预览与测试 --- 💡 如需咨询,请参阅项目文档或提交Issue ## 📚 引用格式 如果您在研究中使用本数据集,请引用以下文献: bibtex @inproceedings{xiong2025youku, title={优酷密集字幕:大规模中文视频密集字幕数据集与基准测试集}, author={Zixuan Xiong, Guangwei Xu, Wenkai Zhang, Yuan Miao, Xuan Wu, LinHai, Ruijie Guo, Hai-Tao Zheng}, booktitle={第十三届国际学习表征会议}, year={2025}, url={https://openreview.net/forum?id=vvi5OjPhbu} } ## 📄 许可证 本数据集采用[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)许可协议发布。 --- <div align="center"> ⭐ 如果您认为本数据集对您有帮助,请在GitHub上为我们点亮Star! ⭐ </div>




