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LapUNet:使用动态拉普拉西亚残余U形网络对单眼深度估计的一种新方法

Yanhui Xi1,2, Sai Li3,4, Zhikang Xu3,4

  • 1School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, Hunan, China. xiyanhui@126.com.

Scientific reports
|October 9, 2024
PubMed
概括

拉普尼特通过引入一种新的动态拉普拉西亚残余U形模块来增强单眼深度估计. 这种方法提高了深度地图细节和边缘清晰度,在基准数据集上表现优于现有的模型.

关键词:
在 ASPP ASPP 上,你会发现.动态拉普拉西安残留物拉普尼特 (LapUNet) 是一个拉普尼特网络.拉普拉斯金字塔是一个拉普拉斯金字塔.单眼深度估计的估计方法

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Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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