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Emotion Recognition Using Transformers with Masked Learning
March 21, 2024, 4:46 a.m. | Seongjae Min, Junseok Yang, Sangjun Lim, Junyong Lee, Sangwon Lee, Sejoon Lim
cs.CV updates on arXiv.org arxiv.org
Abstract: In recent years, deep learning has achieved innovative advancements in various fields, including the analysis of human emotions and behaviors. Initiatives such as the Affective Behavior Analysis in-the-wild (ABAW) competition have been particularly instrumental in driving research in this area by providing diverse and challenging datasets that enable precise evaluation of complex emotional states. This study leverages the Vision Transformer (ViT) and Transformer models to focus on the estimation of Valence-Arousal (VA), which signifies the …
abstract analysis arxiv behavior behavior analysis competition cs.ai cs.cv datasets deep learning diverse driving emotion emotions fields human human emotions recognition research transformers type
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