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README.md
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---
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license: apache-2.0
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---
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# From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos
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<img width="1024" alt="image" src="https://github.com/user-attachments/assets/c629e924-cec2-46c9-9e9a-369b4e6d0aef">
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[](https://paperswithcode.com/sota/dynamic-facial-expression-recognition-on?p=from-static-to-dynamic-adapting-landmark-1)<br>
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[](https://paperswithcode.com/sota/dynamic-facial-expression-recognition-on-dfew?p=from-static-to-dynamic-adapting-landmark-1)<br>
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[](https://paperswithcode.com/sota/dynamic-facial-expression-recognition-on-mafw?p=from-static-to-dynamic-adapting-landmark-1)<br>
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[](https://paperswithcode.com/sota/facial-expression-recognition-on-affectnet?p=from-static-to-dynamic-adapting-landmark-1)<br>
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[](https://paperswithcode.com/sota/facial-expression-recognition-on-raf-db?p=from-static-to-dynamic-adapting-landmark-1)<br>
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>[From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos](https://ieeexplore.ieee.org/document/10663980)<br>
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>Yin Chen$^{†}$, Jia Li$^{†∗}$, Shiguang Shan, Meng Wang, and Richang Hong
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## 📰 News
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**[2024.9.5]** The fine-tuned checkpoints are available.
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**[2024.9.2]** The code and pre-trained models are available.
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**[2024.8.28]** The paper is accepted by IEEE Transactions on Affective Computing.
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**[2023.12.5]** ~~Code and pre-trained models will be released here~~.
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## 🚀 Main Results
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### Dynamic Facial Expression Recognition
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<img width="1024" alt="image" src="https://github.com/user-attachments/assets/2144837d-9fd5-4f88-8447-1f6049b38e9a">
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