Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge
<|reference_start|>Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge: 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.<|reference_end|>
@article{shen2024facial,
    title={Facial Affect Recognition based on Multi Architecture Encoder and
  Feature Fusion for the ABAW7 Challenge},
    author={Kang Shen, Xuxiong Liu, Boyan Wang, Jun Yao, Xin Liu, Yujie Guan, Yu
  Wang, Gengchen Li, Xiao Sun},
    journal={arXiv preprint arXiv:2407.12258},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.12258},
    primaryClass={cs.CV}
}