---
license: apache-2.0

tags:            # 用户自定义标签
  - PPTAnimation
  - PowerPoint
  - video-caption
  - slides-animation
  - Vision-Language
  - synthetic

# 数据模态与任务
multi-modal:
  Video-Captioning:        # 任务名称
    resolutions:
      - 1280 x 720         # 实际视频为 720p
    encoding:
      - mp4
    languages:
      - en
    multilinguality:
      - monolingual

configs:                   # 数据文件配置
  - config_name: default
    data_files:
      - split: videos
        path: "Videos/*.mp4"
      - split: captions
        path: "Captions/*.txt"
---

# PPTAnimation_Test Dataset Card

## 1. Overview
**PPTAnimation_Test** comprises **1,000** synthetic short videos (< 15 s each) of PowerPoint slide animations, paired one-to-one with human-written captions.  
- `Videos/`: MP4 clips named `video_0001.mp4` … `video_1000.mp4`.  
- `Captions/`: Plain-text files (`video_0001.txt`, etc.) that store the **ground-truth natural-language descriptions** of each video.

The dataset is ideal for **vision–language model (VLM)** fine-tuning or evaluation, and it also supports tasks such as **video captioning** and **video understanding**.

## 2. Directory Structure
```bash
PPTAnimation_Test/
├── Videos/
│   ├── video_0001.mp4
│   ├── video_0002.mp4
│   └── ...
└── Captions/
    ├── video_0001.txt
    ├── video_0002.txt
    └── ...
```

## 3. Tasks & Applications
- Vision–language alignment: video–text retrieval, cross-modal understanding

- Video caption generation: produce textual descriptions from animation videos

- VLM fine-tuning / benchmarking: assess a model’s ability to understand PPT animations

## 4. License
This dataset is released under the Apache License 2.0. Please comply with its terms of use.

## 5. Citation
If you use the dataset in academic work, please cite the following paper:
```bibtex
@misc{jiang2025animationneedsattentionholistic,
      title        = {Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Models},
      author       = {Yifan Jiang and Yibo Xue and Yukun Kang and Pin Zheng and Jian Peng and Feiran Wu and Changliang Xu},
      year         = {2025},
      eprint       = {2507.03916},
      archivePrefix= {arXiv},
      primaryClass = {cs.AI},
      url          = {https://arxiv.org/abs/2507.03916},
}
```
## 6. Usage Example

```python
from modelscope.msdatasets import MsDataset

dataset = MsDataset.load(
    dataset_name='jyf9774/PPTAnimation_Test',
    namespace='jyf9774',
    split='train'  # no official split; use 'train' or None
)

sample = dataset[0]
print(sample['text'])        # Caption text
sample['video'].display()    # Preview the video in a notebook
```