tgve_plus

# Dataset Card for the TGVE+ Test Set

## Dataset Description

- **Homepage: https://fdd-video-edit.github.io/**
- **Paper: https://arxiv.org/abs/2403.09334**

### Dataset Summary

We extend the widely used Text Guided Video Editing (TGVE) benchmark with additional editing tasks. The dataset now comprises seven editing tasks in total:
four from the original TGVE and three new tasks, namely (i) object removal (Remove), (ii) object addition (Add), and
(iii) texture alterations (Texture). The new tasks utilize the same 76 videos from the original TGVE benchmark.

Each row in the dataset consists of the instruction, input/output captions, and the relative path of the video in [TGVE](https://drive.google.com/file/d/1D7ZVm66IwlKhS6UINoDgFiFJp_mLIQ0W/view).
For more details please see our [paper](https://arxiv.org/abs/2403.09334) and [project page](https://fdd-video-edit.github.io/).

We'd like to thank [InstructVid2Vid](https://github.com/amazon-science/instruct-video-to-video) for creating instructions for the original TGVE tasks.

### Licensing Information

Licensed with CC-BY-NC 4.0 License available [here](https://creativecommons.org/licenses/by-nc/4.0/legalcode?fbclid=IwAR2SYZjLRywwUMblkWg0LyAxHVVTloIFlvC-ju3BthIYtOM2jpQHgbeXOsM).

### Citation Information
```
@inproceedings{Singer2024VideoEV,
title={Video Editing via Factorized Diffusion Distillation},
author={Uriel Singer and Amit Zohar and Yuval Kirstain and Shelly Sheynin and Adam Polyak and Devi Parikh and Yaniv Taigman},
year={2024},
url={https://api.semanticscholar.org/CorpusID:268385300}
}
```

# TGVE+ 测试集数据集卡片

## 数据集说明
- **主页：https://fdd-video-edit.github.io/**
- **论文：https://arxiv.org/abs/2403.09334**

### 数据集概述
我们对当前广泛使用的**文本引导视频编辑（Text Guided Video Editing, TGVE）**基准测试集进行扩展，新增了多项视频编辑任务。本数据集目前共包含7项编辑任务：其中4项源自原始TGVE基准测试集，另外3项为新增任务，分别是（i）目标移除（Remove）、（ii）目标添加（Add）以及（iii）纹理修改（Texture）。新增任务沿用了原始TGVE基准测试集中的全部76段视频素材。

数据集中的每一条目均包含编辑指令、输入/输出字幕，以及该视频在[TGVE](https://drive.google.com/file/d/1D7ZVm66IwlKhS6UINoDgFiFJp_mLIQ0W/view)资源中的相对路径。如需了解更多细节，请参阅我们的[论文](https://arxiv.org/abs/2403.09334)与[项目主页](https://fdd-video-edit.github.io/)。

我们谨向[InstructVid2Vid](https://github.com/amazon-science/instruct-video-to-video)团队致谢，感谢其为原始TGVE任务生成了编辑指令。

### 授权信息
本数据集采用CC-BY-NC 4.0协议进行授权，协议详情可查阅[此处](https://creativecommons.org/licenses/by-nc/4.0/legalcode?fbclid=IwAR2SYZjLRywwUMblkWg0LyAxHVVTloIFlvC-ju3BthIYtOM2jpQHgbeXOsM)。

### 引用信息

@inproceedings{Singer2024VideoEV,
title={Video Editing via Factorized Diffusion Distillation},
author={Uriel Singer and Amit Zohar and Yuval Kirstain and Shelly Sheynin and Adam Polyak and Devi Parikh and Yaniv Taigman},
year={2024},
url={https://api.s. org/corpusID:268385300}
}

搜集汇总

背景与挑战

背景概述

tgve_plus是TGVE视频编辑基准测试的扩展数据集，新增了物体移除、添加和纹理修改3种任务，共包含7种视频编辑任务，基于76个原始视频构建。数据集提供编辑指令、文本描述和视频路径信息，采用CC-BY-NC 4.0许可协议。