Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.cetys.mx/handle/60000/831
Título : Capsule networks for 3D pose estimation in computer graphics
Autor : Picos, Kenia
Otros Autores: Orozco Rosas, Ulises
Autor: Montemayor, Antonio
Cuesta-Infante, Alfredo
Palabras clave : Video games;Object reconstruction
Sede: Campus Tijuana
Fecha de publicación : mar-2020
Resumen : 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
metadata.dc.description.url: https://www.nvidia.com/content/dam/en-zz/Solutions/gtc/conference-posters/gtc2020-posters/Visualization%20_Rendering_01_P21924_Kenia_Picos_Web.pdf
URI : https://repositorio.cetys.mx/handle/60000/831
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