Sato Laboratory/Sugano Laboratory, UTokyo-IIS

Our group consists of two independent research laboratories (Y. Sato Lab. and Sugano Lab.) working closely together with a focus on computer vision.

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Jury Selections at 24th JAPAN MEDIA ARTS FESTIVAL

AICOM project was chosen as Jury Selections at 24th JAPAN MEDIA ARTS FESTIVAL, Entertainment Division.

Last updated on Mar 23, 2021

Jury Selections at 24th JAPAN MEDIA ARTS FESTIVAL

Featured Publications

Neural Routing by Memory

Recent Convolutional Neural Networks (CNNs) have achieved significant success by stacking multiple convolutional blocks, named …

Kaipeng Zhang, Zhenqiang Li, Zhifeng Li, Wei Liu, Yoichi Sato

Neural Routing by Memory

Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction

Every hand-object interaction begins with contact. Despite predicting the contact state between hands and objects is useful in …

Takuma Yagi, Md Tasnimul Hasan, Yoichi Sato

Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction

Stacked Temporal Attention: Improving First-person Action Recognition by Emphasizing Discriminative Clips

First-person action recognition is a challenging task in video understanding. Because of strong ego-motion and a limited field of view, …

Lijin Yang, Yifei Huang, Yusuke Sugano, Yoichi Sato

Stacked Temporal Attention: Improving First-person Action Recognition by Emphasizing Discriminative Clips

Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data

The human gaze is a cost-efficient physiological data that reveals human underlying attentional patterns. The selective attention …

Yifei Huang, Xiaoxiao Li, Lijin Yang, Lin Gu, Yingying Zhu, Hirofumi Seo, Qiuming Meng, Tatsuya Harada, Yoichi Sato

Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data

Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation

Hand segmentation is a crucial task in first-person vision. Since first-person images exhibit strong bias in appearance among different …

Takehiko Ohkawa, Takuma Yagi, Atsushi Hashimoto, Yoshitaka Ushiku, Yoichi Sato

Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation

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