用voxel-mesh混合表示来实现实时视图合成,通过网格化密度场
IEEE transactions on visualization and computer graphics
|March 3, 2025
概括
本研究介绍了Vosh,一种混合神经辐射场 (NeRF) 方法,将voxel和网状元件结合起来,以实现高效和高质量的新视图合成. 沃什平衡了染速度和细节,在移动设备上实现了实时性能.
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:
- 神经辐射场 (NeRF) 对于新的视图合成是有效的.
- 现有的NeRF表示 (voxel,mesh) 在染质量和速度之间有权衡.
- 需要一种混合方法来结合voxel和网格表示的优势.
研究的目的:
- 提出Vosh,一种新的混合神经辐射表示.
- 为了在视图合成中实现染速度和质量之间的平衡.
- 为了能够灵活地控制质量与速度的权衡.
主要方法:
- 通过优化一个带有神经染的voxel网格开发了Vosh.
- 具有战略意义的网格部分体积密度场.
- 实现了混合染,结合了voxel和网状元件.
- 启用可调节的混合比率,用于用户控制的权衡.
主要成果:
- 沃什在染质量和速度之间取得了值得称赞的平衡.
- 网状元件可以加速简单场景的染.
- 语音组件可以确保复杂区域的高质量染.
- 在移动设备上展示了实时性能.
结论:
- 沃什为新的视图合成提供了灵活和高效的解决方案.
- 混合方法克服了纯 Voxel 或网状 NeRFs 的局限性.
- 沃什可以为各种应用程序提供可适应的染性能.
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