Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IBISML, IPSJ-CVIM |
2024-03-03 09:24 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Fine-grained Activity Recognition with Pretraining State Transitions in Manipulated Objects Atsushi Okamoto, Katsufumi Inoue, Michifumi Yoshioka (Osaka Metropolitan Univ.) PRMU2023-53 |
(To be available after the conference date) [more] |
PRMU2023-53 pp.13-18 |
PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI |
2023-11-16 16:50 |
Tottori |
(Primary: On-site, Secondary: Online) |
Boosting Representation Learning through Combination of Web-based Similar Image Search and Diversity-based Query Strategy Shiryu Ueno, Kunihito Kato (Gifu Univ.) PRMU2023-21 |
(To be available after the conference date) [more] |
PRMU2023-21 pp.32-36 |
BioX |
2023-10-13 10:20 |
Okinawa |
Nobumoto Ohama Memorial Hall |
Discrimination between Real and Generated Gestures of Speakers
-- An Attempt to Improve Generalization Performance in Unseen Generation Methods through Self-Supervised Learning -- Geng Mu (AGU), Naoshi Kaneko (TDU), Kazuhiko Sumi (AGU) BioX2023-67 |
Currently, discerning artificially generated misinformation is a critical societal challenge, with research progressing ... [more] |
BioX2023-67 pp.44-49 |
IBISML |
2023-09-08 13:25 |
Osaka |
Osaka Metropolitan University (Nakamozu Campus) (Primary: On-site, Secondary: Online) |
Consideration of Negative Samples in Contrastive Learning Daiki Ishiguro, Tomoko Ozeki (Tokai Univ.) IBISML2023-28 |
Contrastive learning has achieved accuracy comparable to supervised learning. In this method, the transformed image pair... [more] |
IBISML2023-28 pp.16-21 |
NLC, IPSJ-NL |
2023-03-18 10:25 |
Okinawa |
OIST (Primary: On-site, Secondary: Online) |
NLC2022-20 |
(To be available after the conference date) [more] |
NLC2022-20 pp.7-11 |
MI |
2023-03-07 15:38 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
A Denoising Method for Low Dose CT by Iterative Processing Using Self-Supervised Learning Yuki Sato, Hiroyuki Kudo (Univ of Tsukuba) MI2022-121 |
In recent years, patient exposure has become an issue, and low-dose CT, which reduces the amount of radiation irradiated... [more] |
MI2022-121 pp.192-193 |
SP, IPSJ-SLP, EA, SIP [detail] |
2023-02-28 15:55 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Self-Supervised Learning With Spatial Audio-Visual Recording for Sound Event Localization and Detection Yoto Fujita (Kyoto Univ.), Yoshiaki Bando (AIST), Keisuke Imoto (Doshisha Univ./AIST), Masaki Onihsi (AIST), Yoshii Kazuyoshi (Kyoto Univ.) EA2022-89 SIP2022-133 SP2022-53 |
This paper describes an unsupervised pre-training method for sound event localization and detection (SELD) on multi-chan... [more] |
EA2022-89 SIP2022-133 SP2022-53 pp.78-82 |
SP, IPSJ-SLP, EA, SIP [detail] |
2023-03-01 15:50 |
Okinawa |
(Primary: On-site, Secondary: Online) |
The linguistic influence on speaker verification based on Self-Supervised Learning Tomoka Wakamatsu (Tokyo Metropolitan Univ.), Atsushi Ando (NTT), Sayaka Shiota (Tokyo Metropolitan Univ.), Ryo Masumura (NTT), Hitoshi Kiya (Tokyo Metropolitan Univ.) EA2022-118 SIP2022-162 SP2022-82 |
In recent years, statistical models utilizing Self-Supervised Learning (SSL) have been employed in various fields
It ha... [more] |
EA2022-118 SIP2022-162 SP2022-82 pp.247-252 |
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 |
CAS, MSS, IPSJ-AL [detail] |
2022-11-18 14:05 |
Kochi |
(Primary: On-site, Secondary: Online) |
Unsupervised Representation Learning over Decentralized Federated Learning Haruki Sakurai, Hideya Ochiai, Hiroshi Esaki (Univ. Tokyo) CAS2022-54 MSS2022-37 |
Contrastive Learning is a form of self-supervised learning, a method for learning a general-purpose encoder using a larg... [more] |
CAS2022-54 MSS2022-37 pp.79-82 |
SIP |
2022-08-25 14:33 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Structured Deep Image Prior with Interscale Thresholding Jikai Li, Shogo Muramatsu (Niigata Univ.) SIP2022-55 |
This work proposes a novel image denoising technique inspired by the deep image prior (DIP) method. Our contribution is ... [more] |
SIP2022-55 pp.31-36 |
SIP |
2022-08-26 15:33 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Locally-Structured Unitary Network to Capture Tangent Spaces of Manifold Godage Yasas, Shogo Muramatsu (Niigata Univ.) SIP2022-75 |
This work proposes a unique linear transform, locally-structured unitary network (LSUN), that captures tangent spaces of... [more] |
SIP2022-75 pp.129-133 |
PRMU, IPSJ-CVIM |
2022-03-11 17:10 |
Online |
Online |
PRMU2021-90 |
No English abstract [more] |
PRMU2021-90 pp.186-191 |
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 |
IMQ |
2021-05-28 09:40 |
Online |
Online |
Self-supervised representation learning with grayscale images Yuichiro Sumi, Takuto Kojima (Nagoya Univ.), Kentaro Kutsukake (RIKEN), Tetsuya Matsumoto, Hiroaki Kudo (Nagoya Univ.), Yoshinori Takeuchi (Daido Univ.), Noritaka Usami (Nagoya Univ.) IMQ2021-1 |
Multicrystalline silicon solar cells, which are most commonly used in residential photovoltaic systems, include regions ... [more] |
IMQ2021-1 pp.1-4 |
BioX, CNR |
2021-03-02 14:50 |
Online |
Online |
A Face Identification System Based on Self-Supervised Learning Using Triplet-based Variational Autoencoder Yuta Hagio, Yutaka Kaneko, Yuta Hoshi, Marina Kamimura, Yasuhiro Murasaki, Masao Yamatomo (NHK) BioX2020-46 CNR2020-19 |
In this paper, we propose a face image identification system based on self-supervised learning for IoT devices and compa... [more] |
BioX2020-46 CNR2020-19 pp.32-37 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2021-02-18 17:05 |
Online |
Online |
Design Creation with GAN using features that reflect Shape and Material Shun Matsumura, Kiyoharu Aizawa (UTokyo), Atsushi Honda, Seiji Kurokoshi (DIGISEARCH) ITS2020-34 IE2020-48 |
When designers create a new design, they often refer to the existing design of shapes and materials to create a new desi... [more] |
ITS2020-34 IE2020-48 pp.43-48 |
IBISML |
2020-03-11 11:35 |
Kyoto |
Kyoto University (Cancelled but technical report was issued) |
Pre-training for Action Classification Task Using Video Frame Prediction Task Hidemoto Nakada, Hideki Asoh (AIST) IBISML2019-45 |
Continuous Video frames have strongly correlated with each other and thus include rich information that could be leverag... [more] |
IBISML2019-45 pp.85-90 |
AI |
2011-05-26 16:45 |
Tokyo |
Kwansei Gakuin Univ. Tokyo Marunouchi Campus |
A Proposal for Building Semantic Network by Mining Human Activity from Web Nguyen The Minh, Masahiro Itou, Takahiro Kawamura, Yasuyuki Tahara, Akihiko Ohsuga (UEC, Tokyo) AI2011-8 |
The final goal of this paper is to help computers recommend the most suitable action patterns based on users' behaviors.... [more] |
AI2011-8 pp.39-44 |
AI |
2010-06-25 11:30 |
Tokyo |
|
Automatic Extraction of Human Activity Attributes from Twitter Nguyen Minh The, Takahiro Kawamura, Yasuyuki Tahara, Akihiko Ohsuga (Univ. of Electro-Comm.) AI2010-4 |
The goal of this paper is to describe a method to automatically extract all basic attributes namely actor, action, objec... [more] |
AI2010-4 pp.19-23 |