1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
CALICO: Confident Active Learning with Integrated Calibration
Lorenzo S. Querol, Hajime Nagahara, Hideaki Hayashi
The growing use of deep learning in safety-critical applications, such as medical imaging, has raised concerns about limited labeled data, where this demand is amplified as model c…
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…