SGSNet: A Lightweight Depth Completion Network Based on Secondary Guidance and Spatial Fusion

The depth completion task aims to generate a dense depth map from a sparse depth map and the corresponding RGB image. As a data preprocessing task, obtaining denser depth maps without affecting the real-time performance of downstream tasks is the challenge. In this paper, we propose a lightweight de...

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Detalles Bibliográficos
Autores principales: Chen, Baifan, Lv, Xiaotian, Liu, Chongliang, Jiao, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459817/
https://www.ncbi.nlm.nih.gov/pubmed/36080872
http://dx.doi.org/10.3390/s22176414

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459817/
https://www.ncbi.nlm.nih.gov/pubmed/36080872
http://dx.doi.org/10.3390/s22176414

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