基于Surfel的高斯反向染,用于从单眼视频中快速和可清晰的动态人体重建.
IEEE transactions on pattern analysis and machine intelligence
|August 14, 2025
概括
本研究介绍了基于Surfel的高斯反向化身 (SGIA) 以实现高效,动态的人类化身重建. 在各种照明条件下,SGIA能够实现穿着的化身的现实性重新照明和姿势操纵.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 三维重建的3D重建
背景情况:
- 动态的人类化身重建对娱乐行业至关重要.
- 现有的方法难以准确地重新点亮和高效地染着装的化身.
研究的目的:
- 从单眼视频中开发一种高效,准确的方法来重建可照亮的,动态的,穿着的人类化身.
- 为了提高动态的人类化身的现实性和可控性,用于新的应用.
主要方法:
- 引入了基于Surfel的高斯反向化身 (SGIA) 进行高效的训练和染.
- 集成的基于物理的染 (PBR) 属性和预集成以图像为基础的照明.
- 提出了一个闭塞近似策略和逐步培训材料解和几何精度.
主要成果:
- 对于动态的人类化身来说,SGIA实现了高度精确的物理特性.
- 展示了显著增强的现实的重新照明能力.
- 与现有的基于隐式的技术相比,提供了显著的速度优势.
结论:
- SGIA提供了一个高效和准确的解决方案,用于动态穿着的人类化身重建.
- 该方法可以在各种条件下实现现实的重新照明和姿势操纵.
- SGIA代表了实时3D人类化身技术的重大进步.
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