Deep Spatial-Temporal Neural Network for Dense Non-Rigid Structure from Motion

Dense non-rigid structure from motion (NRSfM) has long been a challenge in computer vision because of the vast number of feature points. As neural networks develop rapidly, a novel solution is emerging. However, existing methods ignore the significance of spatial–temporal data and the strong capacit...

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Detalles Bibliográficos

Autores principales:	Yaming Wang, Minjie Wang, Wenqing Huang, Xiaoping Ye, Mingfeng Jiang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2022-10-01
Colección:	Mathematics
Materias:	dense non-rigid structure from motion weighted spatial constraint layer normalization layers deep spatial–temporal neural
Acceso en línea:	https://www.mdpi.com/2227-7390/10/20/3794
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