Although 3D Gaussian Splatting (3DGS) has recently made progress in 3D human
reconstruction, it primarily relies on 2D pixel-level supervision, overlooking
the geometric complexity and topological relationships of different body parts.
To address this gap, we introduce the Hierarchical Graph Human Gaussian Control
(HUGS) framework for achieving high-fidelity 3D human reconstruction. Our
approach involves leveraging explicitly semantic priors of body parts to ensure
the consistency of geometric topology, thereby enabling the capture of the
complex geometrical and topological associations among body parts.
Additionally, we disentangle high-frequency features from global human features
to refine surface details in body parts. Extensive experiments demonstrate that
our method exhibits superior performance in human body reconstruction,
particularly in enhancing surface details and accurately reconstructing body
part junctions. Codes are available at this https URL

通过引入分层图人体高斯控制（HUGS）框架，基于 3D 高斯喷洒（3DGS）的方法在人体重建方面取得了进展，通过利用身体部位的语义先验来确保几何拓扑的一致性，从而捕捉身体部位之间的复杂几何和拓扑关联，特别擅长增强表面细节和准确重建身体部位连接点。