---
title: cv_rife_video-frame-interpolation
canonical_url: "https://www.modelscope.cn/models/Damo_XR_Lab/cv_rife_video-frame-interpolation"
md_url: "https://www.modelscope.cn/models/Damo_XR_Lab/cv_rife_video-frame-interpolation.md"
repository: Damo_XR_Lab/cv_rife_video-frame-interpolation
chinese_name: "RIFE视频插帧"
last_updated: 2024-03-07
license: "MIT License"
pipeline_tag: video-frame-interpolation
tasks:
  - video-frame-interpolation
library_name:
  - pytorch
frameworks:
  - Pytorch
downloads: 584
stars: 3
tags:
  - Alibaba
  - XR
---

# cv_rife_video-frame-interpolation

> cv_rife_video-frame-interpolation - Damo_XR_Lab 在 ModelScope 开源的模型。输入低帧率视频，输出高帧率视频，让视频更丝滑

Damo_XR_Lab/cv_rife_video-frame-interpolation 是 ModelScope 魔搭社区上的video-frame-interpolation模型，采用 MIT License 许可。

- **Repository**: Damo_XR_Lab/cv_rife_video-frame-interpolation
- **License**: MIT License
- **Tasks**: video-frame-interpolation
- **Tags**: Alibaba, XR
- **Downloads**: 584
- **Stars**: 3
- **Last updated**: 2024-03-07

Source: https://www.modelscope.cn/models/Damo_XR_Lab/cv_rife_video-frame-interpolation

---

#### Clone with HTTP
```bash
 git clone https://www.modelscope.cn/Damo_XR_Lab/cv_rife_video-frame-interpolation.git
```


# 视频插帧介绍

## 任务
给定一段低帧率视频，模型会返回更流畅的高帧率视频（默认为输入帧率两倍）。

## 模型描述

本模型基于**Real-Time Intermediate Flow Estimation for Video Frame Interpolation**，
适用于各类低帧率视频增强，用于提升视频的流畅度，消除卡顿现象。

技术细节请见：
**[[Paper](https://arxiv.org/abs/2011.06294)]** |
**[[Project Page](https://github.com/megvii-research/ECCV2022-RIFE/)]**  <br />


## 代码示例

```python
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.outputs import OutputKeys

video = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/videos/video_frame_interpolation_test.mp4'
video_frame_interpolation_pipeline = pipeline(Tasks.video_frame_interpolation, 'Damo_XR_Lab/cv_rife_video-frame-interpolation')
result = video_frame_interpolation_pipeline(video)[OutputKeys.OUTPUT_VIDEO]
print('pipeline: the output video path is {}'.format(result))
```

## 相关论文以及引用信息
该模型借鉴了以下论文的思路或代码，感谢作者的贡献！
```
@inproceedings{huang2022rife,
  title={Real-Time Intermediate Flow Estimation for Video Frame Interpolation},
  author={Huang, Zhewei and Zhang, Tianyuan and Heng, Wen and Shi, Boxin and Zhou, Shuchang},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  year={2022}
}
```