3D Gaussian Splatting (3DGS) has recently revolutionized radiance field
reconstruction, achieving high quality novel view synthesis and fast rendering
speed without baking. However, 3DGS fails to accurately represent surfaces due
to the multi-view inconsistent nature of 3D Gaussians. We present 2D Gaussian
Splatting (2DGS), a novel approach to model and reconstruct geometrically
accurate radiance fields from multi-view images. Our key idea is to collapse
the 3D volume into a set of 2D oriented planar Gaussian disks. Unlike 3D
Gaussians, 2D Gaussians provide view-consistent geometry while modeling
surfaces intrinsically. To accurately recover thin surfaces and achieve stable
optimization, we introduce a perspective-accurate 2D splatting process
utilizing ray-splat intersection and rasterization. Additionally, we
incorporate depth distortion and normal consistency terms to further enhance
the quality of the reconstructions. We demonstrate that our differentiable
renderer allows for noise-free and detailed geometry reconstruction while
maintaining competitive appearance quality, fast training speed, and real-time
rendering. Our code will be made publicly available.

通过将三维体积转化为一组二维定向平面高斯盘，使用透视准确的二维喷洒过程，结合深度扭曲和法线一致性项，实现从多视角图像中准确重建细表面并提高重建质量的一种方法。