Transformer generative model produces emotional body motions from Japanese motion-capture data, achieving 22.8% machine and 24.9% human recognition accuracy, with demonstrated utility for augmenting recognition models, extracting patterns, and synthesizing transitions.
Survey on emotion recognition through posture detection and the possibility of its application in virtual reality,
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Generative Learning as a Tool to Improve Perception of Emotional Body Motion Expressions
Transformer generative model produces emotional body motions from Japanese motion-capture data, achieving 22.8% machine and 24.9% human recognition accuracy, with demonstrated utility for augmenting recognition models, extracting patterns, and synthesizing transitions.