Self‐supervised monocular depth estimation via asymmetric convolution block

Self‐supervised monocular depth estimation via asymmetric convolution block

Abstract Without the dependence of depth ground truth, self‐supervised learning is a promising alternative to train monocular depth estimation. It builds its own supervision signal with the help of other tools, such as view synthesis and pose networks. However, more training parameters and time cons...

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Bibliographic Details
Main Authors: Lingling Hu, Hao Zhang, Zhuping Wang, Chao Huang, Changzhu Zhang
Format: Article
Language:English
Published: Wiley 2022-06-01
Series:IET Cyber-systems and Robotics
Subjects:
asymmetric convolution block (ACB)
KITTI dataset
self‐supervised depth estimation
Online Access:https://doi.org/10.1049/csy2.12051

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