August 24, 2025SensorsOpen Access

Ada-DF++: A Dual-Branch Adaptive Facial Expression Recognition Method Integrating Global-Aware Spatial Attention and Squeeze-and-Excitation Attention

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The Ada-DF++ model significantly improves facial expression recognition accuracy, reducing background noise and enhancing subtle features.
The model achieved test accuracies of 89.21% on the RAF-DB dataset and outperformed state-of-the-art methods.
This approach integrates global-aware spatial attention and squeeze-and-excitation attention for better model performance.
The findings highlight the importance of enhanced attention mechanisms for effectively distinguishing subtle expression variations.

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Proposed dual-branch architecture improves accuracy in facial expression recognition tasks, indicating the effectiveness of attention mechanisms.

Li et al. (2025) studied this question.

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Proposed dual-branch architecture improves accuracy in facial expression recognition tasks, indicating the effectiveness of attention mechanisms.