Código QR

Fully convolutional multi‐scale dense networks for monocular depth estimation

Monocular depth estimation is of vital importance in understanding the 3D geometry of a scene. However, inferring the underlying depth is ill‐posed and inherently ambiguous. In this study, two improvements to existing approaches are proposed. One is about a clean improved network architecture, for w...

Descrición completa

Gardado en:
Principais autores: Jiwei Liu, Yunzhou Zhang, Jiahua Cui, Yonghui Feng, Linzhuo Pang
Formato: Artigo
Idioma:Inglês
Publicado: Wiley 2019-08-01
Series:IET Computer Vision
Assuntos:
clean improved network architecture
end-to-end fully convolutional multiscale dense networks
dense upsampling blocks
selected skip connection
edge-preserving loss functions
reverse Huber loss
Acceso en liña:https://doi.org/10.1049/iet-cvi.2018.5645
Tags: Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!

Títulos similares