Facial Expression Recognition (FER) is crucial in various fields. This study focuses on enhancing FER through semi-supervised learning and temporal modeling. The limited FER dataset size hinders generalization, prompting the use of pseudo-labels for unlabeled data. A debiased feedback strategy addresses category imbalance and data bias. Introducing a Temporal Encoder captures temporal relationships for dynamic recognition. The method excelled in the 6th ABAW competition, confirming its effectiveness.
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Wichtige Erkenntnisse aus
by Jun Yu,Zhiho... um arxiv.org 03-19-2024
https://arxiv.org/pdf/2403.11942.pdfTiefere Fragen