(Submission to the Affective Behavior Analysis in-the-wild (ABAW) 2021 competition)
This repository presents a multi-task mean teacher model for semi-supervised Affective Behavior Analysis to learn from missing labels and exploring the learning of multiple correlated task simultaneously.
For more detail, please check our paper: Arxiv.
torch 1.6.0, torchaudio 0.6, tqdm, Numpy, OpenCV 4.2.0, lmdb
To predict on competition test set, download our model and alignment files:
Alignment_face,Model Weight,Alignment data can be download here with extract code: wk36
Clone the repository,then download above data and config their path in opts.py before running
python test_val_aff2.py
Our paper have been submitted to Arxiv.
This repository is based on TSAV, thanks to their excellent work. Please cite their paper of TSAV if this respority helps you.