AI RESEARCH
GS^2: Graph-based Spatial Distribution Optimization for Compact 3D Gaussian Splatting
arXiv CS.CV
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ArXi:2604.01884v1 Announce Type: new 3D Gaussian Splatting (3DGS) has nstrated breakthrough performance in novel view synthesis and real-time rendering. Nevertheless, its practicality is constrained by the high memory cost due to a huge number of Gaussian points. Many pruning-based 3DGS variants have been proposed for memory saving, but often compromise spatial consistency and may lead to rendering artifacts.