# MSA-LMC/S2D

<https://repo.masters-masters.com/en/repos/MSA-LMC/S2D>

[Home](https://repo.masters-masters.com/en) › [MSA-LMC](https://repo.masters-masters.com/en/owners/MSA-LMC) › [S2D](https://repo.masters-masters.com/en/repos/MSA-LMC/S2D)

MSA-LMC/S2D has 124 stars on GitHub. Its RepoMasters card: Prototype tier. \[TAFFC 2024\] The official implementation of paper: From Static to Dynamic: Adapting…

| Field | Value |
| --- | --- |
| Owner | [MSA-LMC](https://repo.masters-masters.com/en/owners/MSA-LMC) |
| Stars | 124 |
| Forks | 3 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2023 |
| Topics | adapater, dynamic-facial-expression-recognition, facial-expression-recognition, image-to-video, transfer-learning, affective-computing |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [MSA-LMC/S2D](https://github.com/MSA-LMC/S2D) |

## Repository

\[TAFFC 2024\] The official implementation of paper: From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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