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20242026
most citedMulti-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spotting

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

eess.IV2026

Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models

Niccolò Fineschi, Jovana Panic, Atsushi Watanabe +7

Retinal foundation models have demonstrated strong performance across a wide range of ophthalmic tasks, yet relatively little is known about how disease-related information is repr…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.LG2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…