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Takuma Yagi
Takuma Yagi
Project Researcher, Institute of Industrial Science, The University of Tokyo
Verified email at iis.u-tokyo.ac.jp - Homepage
Title
Cited by
Cited by
Year
Future Person Localization in First-Person Videos
T Yagi, K Mangalam, R Yonetani, Y Sato
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018
1332018
Ego4d: Around the world in 3,000 hours of egocentric video
K Grauman, A Westbury, E Byrne, Z Chavis, A Furnari, R Girdhar, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
472022
Foreground-aware stylization and consensus pseudo-labeling for domain adaptation of first-person hand segmentation
T Ohkawa, T Yagi, A Hashimoto, Y Ushiku, Y Sato
IEEE Access 9, 94644-94655, 2021
42021
GO-finder: a registration-free wearable system for assisting users in finding lost objects via hand-held object discovery
T Yagi, T Nishiyasu, K Kawasaki, M Matsuki, Y Sato
26th International Conference on Intelligent User Interfaces, 139-149, 2021
42021
Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction
T Yagi, MT Hasan, Y Sato
32nd British Machine Vision Conference (BMVC), 2021
12021
Precise Affordance Annotation for Egocentric Action Video Datasets
Z Yu, Y Huang, R Furuta, T Yagi, Y Goutsu, Y Sato
arXiv preprint arXiv:2206.05424, 2022
2022
Object Instance Identification in Dynamic Environments
T Yagi, MT Hasan, Y Sato
arXiv preprint arXiv:2206.05319, 2022
2022
GO-Finder: A Registration-Free Wearable System for Assisting Users in Finding Lost Hand-Held Objects
T Yagi, T Nishiyasu, K Kawasaki, M Matsuki, Y Sato
ACM Transactions on Interactive Intelligent Systems (TiiS), 2022
2022
Egocentric Pedestrian Motion Prediction by Separately Modeling Body Pose and Position
D Wu, T Yagi, Y Matsui, Y Sato
IEICE Technical Report; IEICE Tech. Rep. 119 (481), 39-44, 2020
2020
Egocentric Pedestrian Motion Forecasting for Separately Modelling Pose and Location
D WU, T YAGI, Y MATSUI, Y SATO
Future Person Localization in First-Person Videos: Supplementary Material
T Yagi, K Mangalam, R Yonetani, Y Sato
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