| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "activitynet_captions_train.json" |
| - split: val1 |
| path: "activitynet_captions_val1.json" |
| - split: val2 |
| path: "activitynet_captions_val2.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} |
| } |
| ``` |
