GTAvatar：融合高斯散射与纹理映射以实现可照明和可编辑的高斯头像
GTAvatar: Bridging Gaussian Splatting and Texture Mapping for Relightable and Editable Gaussian Avatars
AI总结：
本文提出一种结合2D高斯散射精度与UV纹理映射直观性的方法，通过高效嵌入局部坐标系到模板网格的UV空间，实现单目视频下的连续可编辑材质头像重建，并利用物理基础反射模型实现照明与编辑。
摘要：
近期高斯散射的进步使逼真头像重建愈加精确，为视觉特效、视频会议和虚拟现实应用打开了大门。然而，传统三角网格方法缺乏直观的可编辑性。本文提出一种方法，结合2D高斯散射的精度与UV纹理映射的直观性。通过高效嵌入每个标准高斯原始体的局部坐标系到模板网格的UV空间的补丁中，我们从单目视频中重建出连续的可编辑材质头像。此外，我们利用高效的基于物理的反射模型，使这些内在材质图能够被照明和编辑。通过与最先进方法的广泛比较，我们展示了重建的准确性、照明结果的质量以及通过纹理映射提供直观控制来修改头像外观和几何体的能力，而无需额外优化。
英文摘要：
Recent advancements in Gaussian Splatting have enabled increasingly accurate reconstruction of photorealistic head avatars, opening the door to numerous applications in visual effects, videoconferencing, and virtual reality. This, however, comes with the lack of intuitive editability offered by traditional triangle mesh-based methods. In contrast, we propose a method that combines the accuracy and fidelity of 2D Gaussian Splatting with the intuitiveness of UV texture mapping. By embedding each canonical Gaussian primitive's local frame into a patch in the UV space of a template mesh in a computationally efficient manner, we reconstruct continuous editable material head textures from a single monocular video on a conventional UV domain. Furthermore, we leverage an efficient physically based reflectance model to enable relighting and editing of these intrinsic material maps. Through extensive comparisons with state-of-the-art methods, we demonstrate the accuracy of our reconstructions, the quality of our relighting results, and the ability to provide intuitive controls for modifying an avatar's appearance and geometry via texture mapping without additional optimization.
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