Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Mariko Isogawa"'
Publikováno v:
IEEE Access, Vol 11, Pp 62932-62941 (2023)
This paper examines an importance rank learning method of objects in urban scenes for assisting visually impaired people. Object detection methods have been used to assist visually impaired people in identifying obstacles in urban scenes, such as car
Externí odkaz:
https://doaj.org/article/42867c8a4b4249d4b3fded160111c5a4
Publikováno v:
IEEE Access, Vol 10, Pp 54957-54968 (2022)
In this paper, we propose a framework for 3D human pose estimation using a single 360° camera mounted on the user’s wrist. Perceiving a 3D human pose with such a simple setup has remarkable potential for various applications (e. g., daily-living a
Externí odkaz:
https://doaj.org/article/57a8328c2dc44c81a3ec2739238ce6ad
Publikováno v:
IEEE Access, Vol 6, Pp 69728-69741 (2018)
This paper proposes a novel approach to image inpainting that optimizes the shape of masked regions given by users. In image inpainting, which removes and restores unwanted regions in images, users draw masks to specify the regions. However, it is wi
Externí odkaz:
https://doaj.org/article/c34bec9c65d04be4a6388baba942c03b
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Publikováno v:
2021 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
ITE Transactions on Media Technology and Applications. 8:100-110
Autor:
Dan Mikami, Kosuke Takahashi, Hiroko Yabushita, Mariko Isogawa, Naoki Saijo, Yoshinori Kusachi
Publikováno v:
The Journal of The Institute of Image Information and Television Engineers. 73:883-888
Publikováno v:
CVPR
We describe a method for 3D human pose estimation from transient images (i.e., a 3D spatio-temporal histogram of photons) acquired by an optical non-line-of-sight (NLOS) imaging system. Our method can perceive 3D human pose by `looking around corners
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a4fcebff9d2ecda811b6f856bd98f4d
http://arxiv.org/abs/2003.14414
http://arxiv.org/abs/2003.14414
Publikováno v:
IEICE Transactions on Information and Systems. :3199-3208
Publikováno v:
International Journal of Computer Vision. 127:1751-1766
This paper proposes a learning-based quality evaluation framework for inpainted results that does not require any subjectively annotated training data. Image inpainting, which removes and restores unwanted regions in images, is widely acknowledged as