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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IPSJ-CVIM 2023-05-19
09:35		 Aichi
(Primary: On-site, Secondary: Online)		 Free-viewpoint Omnidirectional Image Synthesis for Large Scenes
Fuma Yasue, Kazutoshi Akita, Norimichi Ukita (TTI) PRMU2023-8		 Recently, Neural Radiance Fields (NeRF) have been attracting attention as a method for arbitrary viewpoint image generat... [more] PRMU2023-8
pp.39-44
PRMU 2021-10-09
09:00		 Online Online Omni-Directional Image Representation in GAN-based Image Generator
Keisuke Okubo, Takao Yamanaka (Sophia Univ.) PRMU2021-17		 The omni-directional image generation from a snapshot image taken by an ordinary camera has been developed using conditi... [more] PRMU2021-17
pp.5-10
PRMU, IPSJ-CVIM, IPSJ-NL 2021-05-21
10:00		 Online Online Scene Recognition of Omni-Directional Images by Patch-Based CNN
Takumi Hatogai, Takao Yamanaka (Sophia Univ.) PRMU2021-3		 In this paper, a scene recognition method for omni-directional images is proposed using patch-based convolutional neural... [more] PRMU2021-3
pp.13-18
PRMU, BioX 2018-03-18
15:20		 Tokyo   Saliency Map Estimation for Omni-Directional Image Considering Prior Distribution
Tatsuya Suzuki, Takao Yamanaka (Sophia Univ.) BioX2017-50 PRMU2017-186		 In recent years, the Deep Learning techniques have been applied to the estimation of saliency maps, which represent prob... [more] BioX2017-50 PRMU2017-186
pp.85-90
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
13:45		 Toyama   Automatic Initial View Generation for 360 Degree Panoramic Images
Takayuki Hara, Akihiro Kakinuma, Satomi Tanaka, Naohiro Kamijo (Ricoh) PRMU2016-62 IBISML2016-17		 We present an automatic initial view generation method for a 360 degree panoramic image adaptive to the image contents. ... [more] PRMU2016-62 IBISML2016-17
pp.83-88
PRMU, IE, MI, SIP 2016-05-20
10:00		 Aichi   High Accuracy Feature Point Tracking for Omnidirectional Image Sequence
Hiroshi Tada, Koichi Ichige (Yokohama Nat'l Univ.) SIP2016-16 IE2016-16 PRMU2016-16 MI2016-16		 In this paper, we propose a highly accurate feature point tracking method for omnidirectional image sequence. It is diff... [more] SIP2016-16 IE2016-16 PRMU2016-16 MI2016-16
pp.85-90
 Results 1 - 6 of 6  /   
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