This is the official Pytorch implementation of AUFART.
AUFART reconstructs 3D head models sensitive to AU activations from a single monocular in-the-wild face image.
Please refer to the paper preprint for more details.
- AU-feature based reconstruction: We propose a Transformer-based 3D face reconstruction framework that leverages the features of AUs in the frame-based 3D face reconstruction process, explicitly consider-ing their correlations.
- Employing professional AU recognition model: We integrate a state-of-the-art AU feature extraction module for effective AU feature extraction from in-the-wild images.
- Effective architecture: We propose a Transformer encoder-based model that can utilize both image features and AU features.
- Novel loss functions: We design AU-based loss fuctions for training our proposed 3D face reconstruction framework
- for the accurate AU prediction: ME-GraphAU
- for the better skin estimation: TRUST