Hybrid CNN-Transformer Model For Facial Affect Recognition In the ABAW4 Challenge

• URL: http://arxiv.org/abs/2207.10201v1
• Date: Wed, 20 Jul 2022 21:38:47 GMT
• Title: Hybrid CNN-Transformer Model For Facial Affect Recognition In the ABAW4 Challenge
• Authors: Lingfeng Wang, Haocheng Li, Chunyin Liu
• Abstract summary: We propose 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.
• Score: 6.786147929596443
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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