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PDANet: Self-Supervised Monocular Depth Estimation Using Perceptual and Data Augmentation Consistency

In recent studies, self-supervised learning methods have been explored for monocular depth estimation. They minimize the reconstruction loss of images instead of depth information as a supervised signal. However, existing methods usually assume that the corresponding points in different views should...

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Principais autores: Huachen Gao, Xiaoyu Liu, Meixia Qu, Shijie Huang
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2021-06-01
Serier:Applied Sciences
Fag:
self-supervised
depth estimation
low texture
perceptual consistency
data augmentation
Online adgang:https://www.mdpi.com/2076-3417/11/12/5383
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