| language: | |
| - en | |
| license: cc-by-nc-4.0 | |
| task_categories: | |
| - video-to-video | |
| # LongV-EVAL: A Benchmark for Long Video Editing Evaluation | |
| [Paper](https://huggingface.co/papers/2502.05433) | |
| LongV-EVAL is a benchmark dataset designed for evaluating text-driven long video editing methods. It consists of 75 high-quality videos, each approximately one minute long, covering diverse domains such as landscapes, people, and animals. The dataset provides meticulously annotated editing prompts for three aspects: foreground, background, and style, enabling comprehensive evaluation of editing quality, temporal consistency, and semantic alignment. | |
| ## Dataset Structure | |
| The dataset is organized into four folders: | |
| - `videos/`: Contains 75 MP4 files of source videos (original unedited videos). | |
| - `foreground/`: Includes 75 text files with prompts focusing on **foreground object editing** (e.g., changing object attributes or replacing objects). | |
| - `background/`: Includes 75 text files with prompts for **background modification** (e.g., altering scene context or tone). | |
| - `style/`: Includes 75 text files with prompts for **artistic style transfer** (e.g., applying styles like Van Gogh, watercolor, or Picasso). |