HSEmotion Team at ABAW-8 Competition: Audiovisual Ambivalence/Hesitancy, Emotional Mimicry Intensity and Facial Expression Recognition

• URL: http://arxiv.org/abs/2503.10399v1
• Date: Thu, 13 Mar 2025 14:21:46 GMT
• Title: HSEmotion Team at ABAW-8 Competition: Audiovisual Ambivalence/Hesitancy, Emotional Mimicry Intensity and Facial Expression Recognition
• Authors: Andrey V. Savchenko,
• Abstract summary: This article presents our results for the eighth Affective Behavior Analysis in-the-Wild (ABAW) competition.<n>We combine facial emotional descriptors extracted by pre-trained models with acoustic features and embeddings of texts recognized from speech.<n>The video-level prediction of emotional mimicry intensity is implemented by simply aggregating frame-level features and training a multi-layered perceptron.
• Score: 16.860963320038902
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This article presents our results for the eighth Affective Behavior Analysis in-the-Wild (ABAW) competition. We combine facial emotional descriptors extracted by pre-trained models, namely, our EmotiEffLib library, with acoustic features and embeddings of texts recognized from speech. The frame-level features are aggregated and fed into simple classifiers, e.g., multi-layered perceptron (feed-forward neural network with one hidden layer), to predict ambivalence/hesitancy and facial expressions. In the latter case, we also use the pre-trained facial expression recognition model to select high-score video frames and prevent their processing with a domain-specific video classifier. The video-level prediction of emotional mimicry intensity is implemented by simply aggregating frame-level features and training a multi-layered perceptron. Experimental results for three tasks from the ABAW challenge demonstrate that our approach significantly increases validation metrics compared to existing baselines.

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