UniTriSplat: A Unified 3D Gaussian Splatting Framework with Uniform Spherical Rasterization for Universal Cameras

摘要

Existing 3D Gaussian Splatting (3DGS) frameworks rely oncamera-speci_x001C_c rasterization, su_x001B_ering from inconsistent solid-angle sam-pling and degraded performance across heterogeneous camera models(e.g., perspective, _x001C_sheye, omnidirectional). To address this limitation,we propose UniTriSplat, a uni_x001C_ed 3DGS framework for universal camerasthat reformulates Gaussian splatting on the unit sphere via HEALPixdiscretization. Leveraging the equal-area property of HEALPix, we con-struct a spherical sampling grid aligned with the angular resolution ofinput images. We derive the forward rendering and gradient propagationof Gaussians directly in the spherical radian domain, yielding uniform op-timization behavior from narrow-FoV images to full 360-degree panora-mas. To enhance perceptual reconstruction quality, we additionally intro-duce a HEALPix-aware SSIM loss that respects spherical neighborhoodstructure. Extensive experiments across diverse camera models demon-strate that UniTriSplat consistently improves cross-camera generaliza-tion while preserving geometric _x001C_delity and rendering quality. Projectpage: https://yipengzhu0809.github.io/UniTriSplat/