Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge

• URL: http://arxiv.org/abs/2407.12258v2
• Date: Fri, 26 Jul 2024 08:42:10 GMT
• Title: Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge
• Authors: Kang Shen, Xuxiong Liu, Boyan Wang, Jun Yao, Xin Liu, Yujie Guan, Yu Wang, Gengchen Li, Xiao Sun,
• Abstract summary: We present our approach to addressing the challenges of the 7th ABAW competition. The competition comprises three sub-challenges: Valence Arousal (VA) estimation, Expression (Expr) classification, and Action Unit (AU) detection.
• Score: 9.638373386602874
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we present our approach to addressing the challenges of the 7th ABAW competition. The competition comprises three sub-challenges: Valence Arousal (VA) estimation, Expression (Expr) classification, and Action Unit (AU) detection. To tackle these challenges, we employ state-of-the-art models to extract powerful visual features. Subsequently, a Transformer Encoder is utilized to integrate these features for the VA, Expr, and AU sub-challenges. To mitigate the impact of varying feature dimensions, we introduce an affine module to align the features to a common dimension. Overall, our results significantly outperform the baselines.

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