Depth Estimation

Goodbye Traditional Monocular Vision! Depth Anything V2 Achieves 10x More Accurate Depth Estimation!

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Goodbye Traditional Monocular Vision! Depth Anything V2 Achieves 10x More Accurate Depth Estimation!

🫱Click here to join the group chat of 18 sub-fields (🔥Highly recommended)🫲 Paper Title: Depth Anything V2 Authors: Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao Project Address: https://depth-anything-v2.github.io/ Compiled by: xlh Reviewed by: Los Abstract: In monocular depth estimation research, the widely used labeled real images have many … Read more

SPDET: Edge-Aware Self-Supervised Panoramic Depth Estimation Transformer With Spherical Geometry

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SPDET: Edge-Aware Self-Supervised Panoramic Depth Estimation Transformer With Spherical Geometry

Title: SPDET: Edge-Aware Self-Supervised Panoramic Depth Estimation Transformer With Spherical Geometry Edge-Aware Self-Supervised Panoramic Depth Estimation Transformer With Spherical Geometry Authors: Chuanqing Zhuang; Zhengda Lu; Yiqun Wang; Jun Xiao; Ying Wang Source Code Link: https://github.com/zcq15/SPDET Abstract Panoramic depth estimation has become a hot topic in 3D reconstruction technology because it provides an omnidirectional spatial field … Read more

Discussing Position and Scale Issues in CNNs

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Discussing Position and Scale Issues in CNNs

Click on the above“Beginner Learning Vision” to choose to add a Star or “Top” Important content delivered first Source | Zhihu Author | Huang Piao Link | https://zhuanlan.zhihu.com/p/113443895 This article is for academic exchange only. If there is any infringement, please contact for deletion. Introduction Recently, I came across several interesting articles and referred to … Read more

How Do Convolutional Neural Networks Learn Depth Information?

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How Do Convolutional Neural Networks Learn Depth Information?

Click on the above “Beginner’s Visual Learning” and choose to add a Star or “Pin” Heavyweight content delivered at the first time Although this article does not propose new methods, it greatly helps us understand how CNN learns some appearance cues to address visual problems requiring geometric models. First, we know that a monocular camera … Read more