Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IPSJ-CVIM |
2023-05-19 09:20 |
Aichi |
(Primary: On-site, Secondary: Online) |
Learning static NeRF representations from video using 2D segmentation masks Takashi Otonari (Tokyo Univ.), Satoshi Ikehata (NII), Kiyoharu Aizawa (Tokyo Univ.) |
[more] |
|
PRMU, IPSJ-CVIM |
2023-05-19 09:50 |
Aichi |
(Primary: On-site, Secondary: Online) |
Integrating Signed Distance Fields into Text-to-3D Generation Zhuofan Sun, Daichi Horita (Univ. of Tokyo), Satoshi Ikehata (NII), Kiyoharu Aizawa (Univ. of Tokyo) |
[more] |
|
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 15:05 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Measuring the impact of 360° video on users' viewing experience Hayaoki Matsumoto, Mizuki Takenawa, Kiyoharu Aizawa (UTokyo), Satoshi Ikehata (NII) IMQ2022-38 IE2022-115 MVE2022-68 |
Recently, the use of 360-degree contents has been increasing in various fields, such as tourism. The use of 360-degree v... [more] |
IMQ2022-38 IE2022-115 MVE2022-68 pp.109-114 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-03 16:50 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Comic Speaker Detection and Estimation using Scene Graph Yingxuan Li, Kiyoharu Aizawa, Yusuke Matsui (UTokyo) PRMU2022-120 IBISML2022-127 |
For the understanding of comics, there is a need to link the comic text to the speaker automatically. Since traditional ... [more] |
PRMU2022-120 IBISML2022-127 pp.329-334 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 10:15 |
Hokkaido |
Hokkaido Univ. |
Text - Image Fashion Retrieval with Textural Features Daichi Suzuki (Tokyo Univ.), Go Irie (Tokyo Univ of Science), Kiyoharu Aizawa (Tokyo Univ.) ITS2022-43 IE2022-60 |
In this study, we propose a method of pre-processing on a dataset and deep learning to perform fashion retrieval conside... [more] |
ITS2022-43 IE2022-60 pp.11-16 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 13:15 |
Hokkaido |
Hokkaido Univ. |
Constructing an ingredient classification model for automatic calculation of nutritional value and environmental impact from user-generated recipes Yoko Yamakata, Liangyu Wang (UTokyo), Eiji Yamasue (Rits), Akiko Sunto (KUHS), Kiyoharu Aizawa (UTokyo) ITS2022-48 IE2022-65 |
In order to calculate rough nutritional values from recipes, this paper proposes a method to link the list of ingredient... [more] |
ITS2022-48 IE2022-65 pp.29-34 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 13:30 |
Hokkaido |
Hokkaido Univ. |
Semi-automatic dataset construction from user-generated recipes for image recognition based dietary assessment Liangyu Wang, Yoko Yamakata (Utokyo), Akiko Sunto (Kanagawa Univ. of Human Services), Kiyoharu Aizawa (Utokyo) ITS2022-49 IE2022-66 |
[more] |
ITS2022-49 IE2022-66 pp.35-40 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 13:45 |
Hokkaido |
Hokkaido Univ. |
Automatic generation of eating order reports from first-person eating videos Kenshiro Sato, Yoko Yamakata, Kiyoharu Aizawa (UTokyo) ITS2022-50 IE2022-67 |
By automatically generating meal reports used by dietitians for dietary guidance from video footage of meals recorded by... [more] |
ITS2022-50 IE2022-67 pp.41-46 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 14:00 |
Hokkaido |
Hokkaido Univ. |
Prediction of mental state from food images Kei Nakamoto (The Univ. of Tokyo), Sosuke Amano (foo.log), Hiroaki Karasawa (Hongo Software Development), Yoko Yamakata, Kiyoharu Aizawa (The Univ. of Tokyo) ITS2022-51 IE2022-68 |
[more] |
ITS2022-51 IE2022-68 pp.47-52 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 15:30 |
Hokkaido |
Hokkaido Univ. |
A Study on Adaptation Methods for Universal Deep Image Compression Koki Tsubota, Kiyoharu Aizawa (UTokyo) ITS2022-56 IE2022-73 |
In this study, we tackle universal deep image compression, which aims to compress images in arbitrary domains such as li... [more] |
ITS2022-56 IE2022-73 pp.77-82 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-22 10:00 |
Hokkaido |
Hokkaido Univ. |
ITS2022-60 IE2022-77 |
Unsupervised domain adaptation (UDA) is extremely effective for transferring knowledge from a label-rich source domain t... [more] |
ITS2022-60 IE2022-77 pp.101-106 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-22 11:00 |
Hokkaido |
Hokkaido Univ. |
Discussion and user study of displaying 360-degree video that follows RoI Yuuki Sawabe (UTokyo), Satoshi Ikehata (NII), Kiyoharu Aizawa (UTokyo) ITS2022-63 IE2022-80 |
Although 360° video images contain information in all directions, the user's viewing angle is limited, resulting in over... [more] |
ITS2022-63 IE2022-80 pp.118-123 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-22 11:15 |
Hokkaido |
Hokkaido Univ. |
Evaluation Metrics Using Object Detection for Visible and Infrared Image Fusion Jihun Kang, Daichi Horita, Kiyoharu Aizawa (UTokyo) ITS2022-64 IE2022-81 |
We propose a new evaluation measure for the fusion images between visible and infrared images using object detection foc... [more] |
ITS2022-64 IE2022-81 pp.124-129 |
PRMU, IPSJ-CVIM |
2022-03-11 16:40 |
Online |
Online |
Extended Panel Detection and Pixel-Wise Segmentation for Comic Editing Runtian Yu, Hikaru Ikuta, Yusuke Matsui, Kiyoharu Aizawa (UTokyo) PRMU2021-88 |
Comic panel extraction plays a significant role in various tasks such as comic editing. In this research, we first defin... [more] |
PRMU2021-88 pp.175-179 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 11:00 |
Online |
Online |
RecipeLog: Input interface for multimedia recipes with structured instructions Akihisa Ishino, Yoko Yamakata (UTokyo), Hiroaki Karasawa (HSD), Sousuke Amano (foo.log), Kiyoharu Aizawa (UTokyo) |
[more] |
|
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 11:00 |
Online |
Online |
Illustration author style translation using SailormoonRedraw data Keita Awane, Daichi Horita, Hikaru Ikuta, Yusuke Matsui (UTokyo), Naohiro Yanase (BOOK WALKER), Kiyoharu Aizawa (UTokyo) ITS2021-26 IE2021-35 |
The author characteristics of illustrations can be divided into two elements: "what to draw" and "how to draw". The latt... [more] |
ITS2021-26 IE2021-35 pp.7-12 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 11:30 |
Online |
Online |
ITS2021-28 IE2021-37 |
The dynamic range of electronic imaging is orders of magnitudes smaller than that of human vision. To obtain images of h... [more] |
ITS2021-28 IE2021-37 pp.19-24 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 13:00 |
Online |
Online |
Domain Incremental Leaning with Adaptive Loss Functions Takumi Kawashima (UTokyo), Go Irie, Daiki Ikami (NTT), Kiyoharu Aizawa (UTokyo) ITS2021-30 IE2021-39 |
During domain incremental learning of image classification task, the distribution of images continually change, and mode... [more] |
ITS2021-30 IE2021-39 pp.31-36 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 13:15 |
Online |
Online |
Towards Universal Deep Image Compression Koki Tsubota (UTokyo), Hiroaki Akutsu (Hitachi), Kiyoharu Aizawa (UTokyo) ITS2021-31 IE2021-40 |
In this paper, we investigate deep image compression towards universal usage. In image compression, it is desirable to b... [more] |
ITS2021-31 IE2021-40 pp.37-42 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-22 10:45 |
Online |
Online |
ITS2021-46 IE2021-55 |
There has been a tremendous progress in unsupervised domain adaptation (UDA), which aims to transfer knowledge acquired ... [more] |
ITS2021-46 IE2021-55 pp.127-132 |