基于深度可分离卷积的三维模型轻量化处理方法
Lightweight Processing Method for 3D Models Based on Depthwise Separable Convolution
罗育林1
作者信息
- 1. 南方电网数字平台科技(广东)有限公司,广东 深圳 518053
- 折叠
摘要
三维模型轻量化处理方法是指对三维模型进行优化处理,以减少其占用的存储空间和计算资源,从而提高处理速度和系统性能的技术手段.在实际应用中,由于三维模型包含大量的顶点、面片和纹理等数据,需要运用三维模型轻量化技术来减少数据量,以更好地适应各种场景和需求.为此,提出基于深度可分离卷积的三维模型轻量化处理方法,以显著减少模型中的参数数量和计算量.该方法对于提升处理效率和优化系统性能具有重要意义.
Abstract
3D model lightweight processing method refers to the technical means to optimize the processing of 3D models to reduce the storage space and computational resources they occupy,so as to improve the processing speed and system performance.In practical applications,since 3D models contain a large amount of data such as vertices,facets and textures,it is necessary to use 3D model lightweighting techniques to reduce the amount of data in order to better adapt to a variety of scenarios and needs.Therefore,a 3D model lightweight processing method based on depthwise separable convolution is proposed to significantly reduce the number of parameters and computational complexity in the model.This method is of great significance for improving processing efficiency and optimizing system performance.
关键词
深度可分离卷积/轻量化处理/三维模型/卷积神经网络Key words
depthwise separable convolution/lightweight processing/3D model/convolutional neural network引用本文复制引用
出版年
2024
NETL
NSTL
万方数据