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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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Principais autores: Baifan Chen, Xiaotian Lv, Chongliang Liu, Hao Jiao
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2022-08-01
Serier:Sensors
Fag:
depth completion
secondary guidance
spatial fusion
Online adgang:https://www.mdpi.com/1424-8220/22/17/6414
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