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Apr, 2024
基于稀疏点云的无监督占据学习
Unsupervised Occupancy Learning from Sparse Point Cloud
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Amine Ouasfi, Adnane Boukhayma
TL;DR
通过使用基于边界采样的方法和基于熵的优化过程,我们提出一种从稀疏输入中学习占据场的方法,并展示了该方法在隐式形状推断方面相对于基线方法和现有技术的有效性。
Abstract
implicit neural representations
have gained prominence as a powerful framework for capturing complex data modalities, encompassing a wide range from 3D shapes to images and audio. Within the realm of 3D shape representation,
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