Emotion Recognition based on Multi-Task Learning Framework in the ABAW4 Challenge

This repository is the codebase for Multi-Task Learning (MTL) Challenge of the 4th Affective Behavior Analysis in-the-wild (ABAW) competition.

ArXiv paper link: https://arxiv.org/abs/2207.09373

Pretrained Model Download

MAE Model

MAE Model pretrained on the C-MS-Celeb dataset: GoogleDrive | BaiduNetdisk

MAE Model pretrained on the EmotionNet dataset: GoogleDrive | BaiduNetdisk

DenseNet Model

DenseNet Model pretrained on FER+ and AffectNet datasets: GoogleDrive | BaiduNetdisk

IResNet Model

Please contact liuchuanhe@situdata.com to apply for IResNet Model download.

Presentation Slides

Our presentation slides at ECCV 2022: GoogleDrive | BaiduNetdisk