cyinen/S2D

From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos

From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos
Yin Chen$^{†}$, Jia Li$^{†∗}$, Shiguang Shan, Meng Wang, and Richang Hong

📰 News

[2024.9.5] The fine-tuned checkpoints are available.

[2024.9.2] The code and pre-trained models are available.

[2024.8.28] The paper is accepted by IEEE Transactions on Affective Computing.

[2023.12.5] Code and pre-trained models will be released here.

🚀 Main Results

Dynamic Facial Expression Recognition

Static Facial Expression Recognition

Visualization

Fine-tune with pre-trained weights

1、 Download the pre-trained weights from baidu drive or google drive or onedrive, and move it to the ckpts directory.

2、 Run the following command to fine-tune the model on the target dataset.

conda create -n s2d python=3.9
conda activate s2d
pip install -r requirements.txt
bash run.sh

📋 Reported Results and Fine-tuned Weights

The fine-tuned checkpoints can be downloaded from baidu driver or huggingface.

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