Create README.md

README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- text-to-video
+- video-editing
+language:
+- en
+pretty_name: VideoGrain-dataset
+source_datasets:
+  - original
+tags:
+- video editing
+- text-to-video
+- text-to-image
+- Pika
+- video generation
+- Video Generative Model Evaluation
+- Text-to-Video Diffusion Model Development
+- Text-to-Video Prompt Engineering
+- Efficient Video Generation
+
+---
+
+
+<p align="center">
+  <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/teasor.png" width="800">
+</p>
+
+
+# Summary
+This is the dataset proposed in our paper [**VideoGrain: Modulating Space-Time Attention for Multi-Grained Video Editing 
+**](https://arxiv.org/abs/2502.17258) (ICLR 2025).
+
+VideoGrain is a zero-shot method for class-level, instance-level, and part-level video editing.
+
+# Directory
+```
+```
+
+# Download 
+
+### Automatical
+Install the [datasets](https://huggingface.co/docs/datasets/v1.15.1/installation.html) library first, by:
+```
+pip install datasets
+```
+Then it can be downloaded automatically with
+```python
+import numpy as np
+from datasets import load_dataset
+
+dataset = load_dataset("XiangpengYang/VideoGrain-dataset")
+```
+
+# License
+
+This dataset are licensed under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). 
+
+
+# Citation
+```
+@article{yang2025videograin,
+  title={VideoGrain: Modulating Space-Time Attention for Multi-grained Video Editing},
+  author={Yang, Xiangpeng and Zhu, Linchao and Fan, Hehe and Yang, Yi},
+  journal={arXiv preprint arXiv:2502.17258},
+  year={2025}
+}
+```
+
+# Contact
+
+If you have any questions, feel free to contact Xiangpeng Yang (knightyxp@gmail.com).