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Updated: Sep 12, 2025

Photorealistic Learned Landscapes for Augmented Reality
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Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

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一个物理信息神经网络框架,通过表面重建解决点云上的PDEs

Junseung Ryu1, Seungtae Park2, Hyung Ju Hwang3

  • 1Department of Mathematics, POSTECH, Pohang, Gyeongsangbuk-do, 37673, Republic of Korea.

Neural networks : the official journal of the International Neural Network Society
|August 7, 2025
PubMed
概括

本研究介绍了一种新的物理信息神经网络 (PINN),用于仅使用点云在3D表面上解决部分微分方程 (PDEs). 这种新的方法绕过了对几何先验的需求,提供了更快,更准确的模拟.

关键词:
几何深度学习的几何深度学习隐含的表面表示表示.规范化流量的流量.在点云上的部分微分方程.基于物理学的神经网络.表面重建的重建.

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