# hzwer/ECCV2022-RIFE

<https://repo.masters-masters.com/en/repos/hzwer/ECCV2022-RIFE>

[Home](https://repo.masters-masters.com/en) › [hzwer](https://repo.masters-masters.com/en/owners/hzwer) › [ECCV2022-RIFE](https://repo.masters-masters.com/en/repos/hzwer/ECCV2022-RIFE)

hzwer/ECCV2022-RIFE has 5,640 stars on GitHub. Its RepoMasters card: Stable tier. ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame…

| Field | Value |
| --- | --- |
| Owner | [hzwer](https://repo.masters-masters.com/en/owners/hzwer) |
| Stars | 5,640 |
| Forks | 568 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2020 |
| Topics | video-interpolation, computer-vision, slomo-filter, deep-learning, aigc |
| Tier | [Stable (5,000 to 19,999 ★)](https://repo.masters-masters.com/en/ranks/cult) |
| View on GitHub | [hzwer/ECCV2022-RIFE](https://github.com/hzwer/ECCV2022-RIFE) |

## Repository

ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame Interpolation

The tier for repos with 5,000 to 19,999 ★. Published odds per card pulled: 0.9%. Rarity: Very rare.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.