Rethinking Pseudo-Labeling for Semi-Supervised Facial Expression Recognition With Contrastive Self-Supervised Learning
Self-supervised learning for semi-supervised facial expression recognition aims to avoid the need to collect expensive labeled facial expression data. Existing methods demonstrate an impressive performance boost, but they artificially assume that small labeled facial expression data and large unlabe...
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| Autores principales: | , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
IEEE
2023-01-01
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| Colección: | IEEE Access |
| Materias: | |
| Acceso en línea: | https://ieeexplore.ieee.org/document/10121455/ |
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