|
|
--- |
|
|
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 |
|
|
--- |
|
|
|
|
|
[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) |
|
|
|
|
|
--- |
|
|
|
|
|
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} |
|
|
} |
|
|
``` |
