Create README.md

README.md

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+---
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: "activitynet_captions_train_rewritten.json"
+  - split: val1
+    path: "activitynet_captions_val1_rewritten.json"
+  - split: val2
+    path: "activitynet_captions_val2_rewritten.json"
+task_categories:
+- text-to-video
+- text-retrieval
+- video-classification
+language:
+- en
+size_categories:
+- 10K<n<100K
+---
+## About
+
+[ActivityNet Captions](https://openaccess.thecvf.com/content_iccv_2017/html/Krishna_Dense-Captioning_Events_in_ICCV_2017_paper.html) contains 20K long-form videos (180s as average length) from YouTube and 100K captions. Most of the videos contain over 3 annotated events. We follow the existing works to concatenate multiple short temporal descriptions into long sentences and evaluate ‘paragraph-to-video’ retrieval on this benchmark.
+
+We adopt the official split:  
+- **Train:**  10,009 videos, 10,009 captions (concatenate from 37,421 short captions)  
+- **Test (Val1):** 4,917 videos, 4,917 captions (concatenate from 17,505 short captions)  
+- **Val2:** 4,885 videos, 4,885 captions (concatenate from 17,031 short captions)  
+
+---
+
+## Get Raw Videos
+
+```bash
+cat ActivityNet_Videos.tar.part-* | tar -vxf -
+```
+
+---
+
+## Official Release
+
+ActivityNet Official Release: [ActivityNet Download](http://activity-net.org/download.html)
+
+---
+
+## 🌟 Citation
+
+```bibtex
+@inproceedings{caba2015activitynet,
+  title={Activitynet: A large-scale video benchmark for human activity understanding},
+  author={Caba Heilbron, Fabian and Escorcia, Victor and Ghanem, Bernard and Carlos Niebles, Juan},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year={2015}
+}
+```