NeuMesh++: 实现多功能和高效的体积编辑,使用基于解的神经网的隐性场.
IEEE transactions on pattern analysis and machine intelligence
|August 19, 2025
概括
这项研究引入了一种新的基于网状神经染方法,它将几何,纹理和语义解脱为高级3D场景编辑. 该技术可以实现全面的编辑,如纹理交换和语义引导的修改,改善现有的神经染限制.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 人工智能的人工智能
背景情况:
- 神经隐性染在新视图合成和3D重建方面表现出色.
- 当前的神经染方法的编辑能力有限,限制用户进行严格的转换或特定类别的编辑.
研究的目的:
- 为全面的3D场景编辑开发一种新的基于网状神经染表示.
- 为了实现超越现有方法的高效和多功能编辑功能.
主要方法:
- 在网状顶点上编码神经辐射场与解散的几何,纹理和语义代码.
- 开发技术,包括局部空间参数化,可学习的顶点颜色修改,空间意识优化和语义辅助区域选择.
主要成果:
- 实现了高效和全面的编辑,包括网格引导的几何编辑,纹理交换,填充,绘画和语义引导的编辑.
- 在真实和合成数据集上展示了卓越的表示质量和编辑能力.
结论:
- 拟议的基于网状神经染方法为3D场景提供了强大而灵活的编辑功能.
- 这种方法显著提升了用于交互式场景操纵的神经染的最新技术.
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