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All Technical Committee Conferences (Searched in: Recent 10 Years)
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| Search Results: Conference Papers |
| Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| KANSAI |
2024-12-22
13:30 |
Osaka |
Osaka Metropolitan University, I-site Namba |
Continuity Video-to-Video style transfer using Stable Diffusion Models
YU HAO, Liu JiaQing, Li YinHao, Chen YanWei (ISSE) |
Video Style Transformation with Stable Diffusion Model**
Yu Hao† Liu Jiaqiang† Li Yinhao† Chen Yanwei†
† College o... [more] |
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| ME |
2024-02-10
10:15 |
Online |
online |
Examination of improvement in product region extraction based on deep neural network
Riku Kato, Takuya Futagami (AGU) |
In this paper, we propose a method, which can extract product regions at pixel-wise level from images uploaded to online... [more] |
ME2024-3
pp.8-11 |
| AIT, IIEEJ, AS, CG-ARTS |
2019-03-12
13:00 |
Tokyo |
Waseda Univ. |
Diminished Reality in Textureless Scenes
Yuka Namboku, Hiroki Takahashi (UEC) |
Diminished Reality (DR), which removes real objects visually, is expected in various scenes. It is, however, difficult t... [more] |
AIT2019-70
pp.81-84 |
| ME |
2017-02-18
14:00 |
Kanagawa |
Kanto Gakuin Univ. |
Consideration of amount of gather that is easy to recognize fabric texture
-- Investigation of differences for sales style and subject group --
Shuntaro Fujita, Tomoharu Ishikawa (Utsunomiya Univ), Yoshiko Yanagida (Bunka Gakuen Univ), Kazuya Sasaki (Utsunomiya Univ), Keiko Miyatake (Kyoritsu Women's Univ), Miyoshi Ayama (Utsunomiya Univ) |
In online shopping, it is regarded as a problem that the texture of the real fabric is hard to be transmitted.
Therefo... [more] |
ME2017-15
pp.55-58 |
| HI, IEICE-IE, AIT, IEICE-ITS, ME, MMS, CE [detail] |
2016-02-22
11:30 |
Hokkaido |
Hokudai |
Text Line Formation Method using Stroke-width of Character Candidates in Scene Images
Rei Endo, Yoshihiko Kawai, Hideki Sumiyoshi (NHK) |
Broadcasters have huge amount of video archive. An image retrieval system based on name of person/place which reflected ... [more] |
MMS2016-1 CE2016-1 HI2016-1 ME2016-34 AIT2016-1
pp.47-50 |
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