Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIP |
2024-03-21 14:25 |
Ibaraki |
Center for Computational Sciences, University of Tsukuba |
Bunch of Tricks for Improving Shuttlecock Detection from Badminton Videos Muhammad Abdul Haq (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU) |
Accurate identification of the shuttlecock is necessary for video analysis in badminton matches, but, it remains difficu... [more] |
SIP2024-4 pp.8-11 |
SIP |
2024-03-21 15:00 |
Ibaraki |
Center for Computational Sciences, University of Tsukuba |
Walking training support method for mountain climbing using foot pressure distribution Satoshi Shimada, Noji Raito, Meguro DAaiki (Nihon Univ.) |
In recent years, many mountaineers are unassociated, and this is a major factor in the increase of accidents. 35 percent... [more] |
SIP2024-5 pp.12-15 |
AIT, IIEEJ, AS, CG-ARTS |
2024-03-05 13:42 |
Tokyo |
Tokyo University of Technology |
Development of a Diagnostic Support System for Intranasal Disease Kaho Ukai, Youngha Chang, Nobuhiko Mukai (TCU), Kojiro Hirano, Kouzou Murakami (SUSM/SUH) |
In this research, a support system has been developed to diagnose whether an endoscopic image shows "severely abnormal n... [more] |
AIT2024-70 pp.135-138 |
AIT, IIEEJ, AS, CG-ARTS |
2024-03-05 14:30 |
Tokyo |
Tokyo University of Technology |
Study on the Impact of Biological Functions and Personality Traits on Shooting Operations in FPS Games Ryotaro Arai, Tomokazu Ishikawa (Toyo Univ.) |
This paper analyzes the effects of players' biological functions and personality traits on shooting maneuvers in order t... [more] |
AIT2024-119 pp.301-302 |
IEICE-ITS, IEICE-IE, ME, AIT, MMS [detail] |
2024-02-19 13:45 |
Hokkaido |
Hokkaido Univ. |
Efficient Human Pose and Shape Estimation using Decomposed Manhattan Self-Attention Yushan Wang, Botao Zhang (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU) |
HMR2.0, a high performance human pose and shape estimation algorithm, leverages ViT as its backbone and uses pretrained ... [more] |
MMS2024-9 ME2024-25 AIT2024-9 pp.44-48 |
BCT, IEEE-BT |
2024-02-16 10:50 |
Aichi |
Nagoya International Center (Primary: On-site, Secondary: Online) |
Adapter-Based Fine-Tuning for Multi-Task Learning Based CSI Feedback in FDD Massive MIMO Systems Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ) |
A multi-task learning-based Channel State Information (CSI) feedback has been proposed to obtain the CSI of the downlink... [more] |
BCT2024-27 pp.25-28 |
IST |
2023-06-21 14:10 |
Tokyo |
Tokyo University of Science Morito Memorial Hall |
[Poster Presentation]
Verification of the effectiveness of multitask learning for demosaicking and white-balancing Yuki Nakagomi, Ryoya Takeuchi, Taishi Iriyama, Takashi Komuro (Saitama Univ) |
In this study, we conducted an investigation on the learning effectiveness of jointly training demosaicking and white ba... [more] |
IST2023-25 pp.19-22 |
IEICE-HIP, HI, VRPSY [detail] |
2023-02-22 14:45 |
Toyama |
(Primary: On-site, Secondary: Online) |
Change of color categories induced by color discrimination learning Takehiro Nagai, Suzuha Horiuchi (Tokyo Tech) |
We examined the effects of perceptual learning of color discrimination on various color perception properties. The obser... [more] |
HI2023-3 pp.45-48 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 14:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Improvement of Binauralization Performance Based on Multi-view Learning on 360° Videos Masaki Yoshida, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we propose a binaural audio generation method based on multi-view learning using 360◦ videos. Conventiona... [more] |
MMS2023-13 ME2023-33 AIT2023-13 pp.65-69 |
ME, SIP, TOKAI |
2022-12-07 13:35 |
Aichi |
(Primary: On-site, Secondary: Online) |
Skeleton Estimation for Swing based on Deep Model by Introducing Articulation Constraints into Training Atsuki Sakata, Shogo Kihira, Nobutaka Shimada (Ritsumeikan Univ.), Yuki Nagano, Masahiki Ueda (SRI) |
For the purpose of developing the automatic diagnosis system of players' golf swing, we propose a method for estimating ... [more] |
ME2022-91 SIP2022-10 pp.23-26 |
ME, SIP, TOKAI |
2022-12-07 15:00 |
Aichi |
(Primary: On-site, Secondary: Online) |
Comparison of gazing points and gaze prediction of midfielders in soccer training
-- for professional and college student soccer players -- Ryo Isa, Kyosuke Horio, Tsubasa Hirakawa, Takayoshi yamashita, Hironobu Fujiyoshi (Chubu Univ.) |
Gaze behavior in sports has received widespread attention. The purpose is to quantitatively analyze and compare the eye ... [more] |
ME2022-94 SIP2022-13 pp.35-38 |
BCT, IEICE-SIS |
2022-10-14 10:00 |
Aomori |
Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Robust Semi-Supervised Learning for Noisy Labels Using Early-learning Regularization and Weighted Loss Ryota Higashimoto, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) |
Training Deep Neural Networks (DNNs) on datasets with incorrect labels (label noise) is an important challenge. In the p... [more] |
|
AIT, IIEEJ, AS, CG-ARTS |
2022-03-08 13:16 |
Online |
Online |
Semi-automatic Manga Colorization Using Flat Colored Images Yugo Shimizu (TUS), Ryosuke Furuta (UTokyo), Delong Ouyang, Yukinobu Taniguchi (TUS), Ryota Hinami, Shonosuke Ishiwatari (Mantra) |
To create color comics, manual colorization process is required, which incurs high labor costs. To solve the problem, we... [more] |
AIT2022-67 pp.115-118 |
AIT, IIEEJ, AS, CG-ARTS |
2022-03-08 13:28 |
Online |
Online |
Style-invariant representations and frame-aware constraints for manga face image clustering Shunta Komatsu (TUS), Ryosuke Furuta (UTokyo), Yukinobu Taniguchi (TUS), Ryota Hinami, Shonosuke Ishiwatari (Mantra) |
Character recognition in manga is an important task to improve the usability of e-comics through recommendation systems ... [more] |
AIT2022-78 pp.153-156 |
AIT, IIEEJ, AS, CG-ARTS |
2022-03-08 13:50 |
Online |
Online |
An Experimental Study on Estimating Residual Quantity of Foodstuff based on Deep Learning using 3D Model Hiromu Takata, Syuhei Sato, Shangce Gao, Zheng Tang (Univ. Of Toyama) |
With the recent development of deep learning techniques, many image recognition methods have been proposed for various o... [more] |
AIT2022-147 pp.393-394 |
HI, IEICE-HIP, ASJ-H, VRPSY [detail] |
2022-02-27 14:15 |
Online |
on line |
A time-series learning model for estimating the microsaccade segments from fixation eye movement data Tomoaki Morimoto, Kousuke Nakagaki, Masahito Sakaguchi, Ryoma Kobata, Hisashi Yoshida, Takeshi Kohama (Kindai Univ.) |
In this study, we constructed a time-series learning model with the structure of Bi-LSTM for fixation eye movement data ... [more] |
HI2022-4 pp.33-38 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 12:45 |
Online |
online |
Regularizing Generative Adversarial Networks with Internal Representation of Generators Yusuke Hara, Toshihiko Yamasaki (UTokyo) |
In training generative adversarial networks, maintaining the criteria of the discriminator stably is crucial to training... [more] |
|
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 13:15 |
Online |
online |
Towards Universal Deep Image Compression Koki Tsubota (UTokyo), Hiroaki Akutsu (Hitachi), Kiyoharu Aizawa (UTokyo) |
In this paper, we investigate deep image compression towards universal usage. In image compression, it is desirable to b... [more] |
|
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 14:25 |
Online |
online |
A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
The prediction of visual sentiment can be useful to understand users' behaviors. Emotion theories underlying the sentime... [more] |
MMS2022-24 ME2022-49 AIT2022-24 pp.171-175 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 15:05 |
Online |
online |
A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a personalized saliency map (PSM) prediction method using a small amount of gaze data based on user ... [more] |
MMS2022-26 ME2022-51 AIT2022-26 pp.181-186 |