CVJul 20, 2022
Hybrid CNN-Transformer Model For Facial Affect Recognition In the ABAW4 Challenge
arXiv:2207.10201v18 citationsh-index: 7
Originality Synthesis-oriented
AI Analysis
This work addresses facial affect recognition for emotion analysis applications, but it is incremental as it builds on existing CNN and Transformer methods.
The paper tackled facial affect recognition by proposing a hybrid CNN-Transformer model for the ABAW4 competition, achieving better performance than the baseline on the validation dataset.
This paper describes our submission to the fourth Affective Behavior Analysis (ABAW) competition. We proposed a hybrid CNN-Transformer model for the Multi-Task-Learning (MTL) and Learning from Synthetic Data (LSD) task. Experimental results on validation dataset shows that our method achieves better performance than baseline model, which verifies that the effectiveness of proposed network.