  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-correct 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.
