Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Songmin Dai"'
Publikováno v:
IET Computer Vision, Vol 15, Iss 4, Pp 312-321 (2021)
Abstract Among all digital representations we have for real physical objects, three‐dimensional (3D) is arguably the most expressive encoding. But due to the limitations of 3D scanning equipment, point cloud often becomes sparse or partially missin
Externí odkaz:
https://doaj.org/article/a56d95db6a8e4ef79983d6fd335814e5
Publikováno v:
IET Computer Vision, Vol 14, Iss 2, Pp 59-64 (2020)
Detecting objects at vastly different scales is a fundamental challenge in computer vision. To solve this, some approaches (e.g. TridentNet) investigate the effect of receptive fields, whereas other approaches (e.g. SNIP, SNIPER) are based on the ima
Externí odkaz:
https://doaj.org/article/e09e65d4e2e843088130a90271ffd42b
Publikováno v:
Future Internet, Vol 11, Iss 2, p 45 (2019)
The tooth-marked tongue is an important indicator in traditional Chinese medicinal diagnosis. However, the clinical competence of tongue diagnosis is determined by the experience and knowledge of the practitioners. Due to the characteristics of diffe
Externí odkaz:
https://doaj.org/article/7c7a5188bfd147f497bc1e1df9a14107
Publikováno v:
Applied Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::666094421d535366d7a3b2e002baaf5a
https://doi.org/10.1007/s10489-023-04569-6
https://doi.org/10.1007/s10489-023-04569-6
Publikováno v:
IET Computer Vision. 14:59-64
Detecting objects at vastly different scales is a fundamental challenge in computer vision. To solve this, some approaches (e.g. TridentNet) investigate the effect of receptive fields, whereas other approaches (e.g. SNIP, SNIPER) are based on the ima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ab26033fcdefd76317e254016353708
https://doi.org/10.1049/iet-cvi.2019.0461
https://doi.org/10.1049/iet-cvi.2019.0461
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::339001e41c3238ee896582d4b38440d7
https://doi.org/10.2139/ssrn.4292741
https://doi.org/10.2139/ssrn.4292741
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddd0bd823104d38f9bd9e78f6b3f6cd1
https://doi.org/10.1109/iccv48922.2021.01154
https://doi.org/10.1109/iccv48922.2021.01154
Publikováno v:
AAAI
An instance with a bad mask might make a composite image that uses it look fake. This encourages us to learn segmentation by generating realistic composite images. To achieve this, we propose a novel framework that exploits a new proposed prior calle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4d10adabdce093955a8879f2a425c0d
https://doi.org/10.1609/aaai.v33i01.33013429
https://doi.org/10.1609/aaai.v33i01.33013429
Publikováno v:
ICME
In this paper, we propose a self-training based method for semi-supervised semantic segmentation. Our method utilizes k perturbed images of each unlabeled image to generate a new mask through the proposed vote operation which in turn is used as a sup
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4138c0077ad3e598e5b7586436db3f7
https://doi.org/10.1109/icme46284.2020.9102851
https://doi.org/10.1109/icme46284.2020.9102851
Publikováno v:
Pattern Recognition. 122:108325
In facial landmark localization tasks, various occlusions heavily degrade the localization accuracy due to the partial observability of facial features. This paper proposes a structural relation network (SRN) for occlusion-robust landmark localizatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33580a7aafe98993ed4da9438ea570c2
https://doi.org/10.1016/j.patcog.2021.108325
https://doi.org/10.1016/j.patcog.2021.108325