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Aug, 2023
DS-Depth: 动态和静态深度估计通过融合代价体积
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume
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Xingyu Miao, Yang Bai, Haoran Duan, Yawen Huang, Fan Wan...
TL;DR
我们提出了一种新颖的自监督单眼深度估计方法,使用动态成本体积来处理静态环境中的移动物体,通过静态和动态成本体积互补来改善深度图的准确性,并采用金字塔蒸馏损失和自适应光度误差损失来提高精度。实验证明,我们的模型在自监督单眼深度估计方面优于先前发布的基线模型。
Abstract
self-supervised monocular depth estimation
methods typically rely on the
reprojection error
to capture geometric relationships between successive frames in static environments. However, this assumption does not h
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