Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 10:45 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
A Note on Multi-label Image Classification in Animation Illustration Considering Hierarchical Relationships of Attributes Ziwen Lan, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a multi-label classification of animated illustrations considering the hierarchical relationships of... [more] |
MMS2023-2 ME2023-22 AIT2023-2 pp.5-9 |
ME |
2021-12-13 14:00 |
Online |
online (Online) |
Emotion Recognition from Gait Using Attention Spatial-Temporal Graph Convolutional Network Shoji Kisita, Chen Yen-Wei (Ritsumeikan Univ.), Tomoko Tateyama (Shiga Univ.), Yutaro Iwamoto, Liu Jiaqing, Chai Shurong (Ritsumeikan Univ.) |
3D pose recognition is a technology that has been used in many fields, including touchless operation in the medical fiel... [more] |
ME2021-94 pp.25-28 |
HI |
2021-03-05 14:30 |
Online |
(Online) |
[Short Paper]
3D Human Body Pose Estimation Using Graph Convolutional Networks Shoji Kisita, Jiaqing Liu (Ritsumeikan Univ.), Tomoko Tateyama (Shiga Univ.), Yutaro Iwamoto, Yen-Wei Chen (Ritsumeikan Univ.) |
3D pose recognition can apply for many fields, such as touchless operation in the medical field and the entertainment fi... [more] |
HI2021-8 pp.27-28 |
AIT, IIEEJ, AS, CG-ARTS |
2019-03-12 15:45 |
Tokyo |
Waseda Univ. (Tokyo) |
Semantic Segmentation for 3D Human Models Satoshi Yamaguchi, Yoshihiro Kanamori, Jun Mitani (University of Tsukuba) |
We propose a technique for semantic segmentation of 3D human models. Existing techniques for general 3D objects solely r... [more] |
AIT2019-80 pp.119-122 |
ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] |
2019-02-20 13:30 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
Evaluation of Multi-level Data Demodulation Using Convolutional Neural Networks for Holographic Data Storage Yutaro Katano, Tetsuhiko Muroi, Nobuhiro Kinoshita, Norihiko Ishii (NHK) |
Holographic data storage (HDS) is a promising next generation archival memory with large capacity, high data-transfer ra... [more] |
MMS2019-20 HI2019-20 ME2019-42 AIT2019-20 pp.205-208 |
IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-16 13:15 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
Suppression of Inter-symbol Interference by Convolutional Neural Networks for Holographic Data Storage Yutaro Katano, Tetsuhiko Muroi, Kinoshita Nobuhiro, Norihiko Ishii (NHK) |
Holographic data storage (HDS) is a promising for next generation archival media. In reproduction, reproduced data of tw... [more] |
MMS2018-25 HI2018-25 ME2018-25 AIT2018-25 pp.267-270 |