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Point-Supervised Facial Expression Spotting with Gaussian-Based Instance-Adaptive Intensity Modeling
Yicheng Deng, Hideaki Hayashi, Hajime Nagahara
Automatic facial expression spotting, which aims to identify facial expression instances in untrimmed videos, is crucial for facial expression analysis. Existing methods primarily…
Enhancing Ambiguous Dynamic Facial Expression Recognition with Soft Label-based Data Augmentation
Ryosuke Kawamura, Hideaki Hayashi, Shunsuke Otake +2
Dynamic facial expression recognition (DFER) is a task that estimates emotions from facial expression video sequences. For practical applications, accurately recognizing ambiguous…
MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition
Ryosuke Kawamura, Hideaki Hayashi, Noriko Takemura +1
Dynamic facial expression recognition (DFER) is an important task in the field of computer vision. To apply automatic DFER in practice, it is necessary to accurately recognize ambi…
SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting
Yicheng Deng, Hideaki Hayashi, Hajime Nagahara
Facial expression spotting, identifying periods where facial expressions occur in a video, is a significant yet challenging task in facial expression analysis. The issues of irrele…
Multi-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spotting
Yicheng Deng, Hideaki Hayashi, Hajime Nagahara
Facial expression spotting is a significant but challenging task in facial expression analysis. The accuracy of expression spotting is affected not only by irrelevant facial moveme…