3 papers
cs.CV2026
PocketGS: On-Device Training of 3D Gaussian Splatting for High Perceptual Modeling
Wenzhi Guo, Guangchi Fang, Shu Yang +1
While 3D Gaussian Splatting (3DGS) enables real-time rendering, its training demands workstation-level compute and memory, making mobile deployment impractical under minute-scale t…
cs.CV2026
Efficient Scene Modeling via Structure-Aware and Region-Prioritized 3D Gaussians
Guangchi Fang, Bing Wang
Reconstructing 3D scenes with high fidelity and efficiency remains a central pursuit in computer vision and graphics. Recent advances in 3D Gaussian Splatting (3DGS) enable photore…
cs.CV2024
Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians
Guangchi Fang, Bing Wang
In this study, we explore the challenge of efficiently representing scenes with a constrained number of Gaussians. Our analysis shifts from traditional graphics and 2D computer vis…