Capsule networks for 3D pose estimation in computer graphics

dc.contributor.author	Picos, Kenia
dc.contributor.author	Orozco Rosas, Ulises
dc.contributor.author	Cuesta-Infante, Alfredo
dc.contributor.author	Sanz, Antonio
dc.contributor.author	Pantrigo, Juan José
dc.coverage.spatial	Silicon, Valley,USA	es_ES
dc.date.accessioned	2022-09-13T00:38:37Z
dc.date.available	2022-09-13T00:38:37Z
dc.date.issued	2020-03
dc.description.abstract	Pose estimation is an important task for novel engineering applications, such as virtual and augmented reality (VR/AR), pose-based video games, object reconstruction, target tracking, driving assistance and recent sports analytics. Commonly, an efficient pose estimation system depends on the pose visualization given by a 3D configuration of location, orientation, and scaling parameters of the target. In this work we implement Capsule Networks to solve 3D pose estimation in computer graphics of rigid objects using a multi-GPU architecture	es_ES
dc.identifier.other	P21924
dc.identifier.uri	https://repositorio.cetys.mx/handle/60000/1468
dc.language.iso	en_US	es_ES
dc.rights	Atribución-NoComercial-CompartirIgual 2.5 México	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/2.5/mx/	*
dc.subject	Capsule networks	es_ES
dc.subject	3D pose estimation	es_ES
dc.subject.sede	Campus Tijuana	es_ES
dc.title	Capsule networks for 3D pose estimation in computer graphics	es_ES
dc.type	Presentation	es_ES

Files

Now showing 1 - 1 of 1