7 papers
SkelMo: Universal Skeletal Motion Generation for 3D Rigged Shapes
Ye Tao, Yuxin Yao, Kendong Liu +2
Motion generation for rigged shapes is vital for scalable 4D asset production. However, template-based methods are limited by specific topologies and fail to generalize across dive…
From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data
Yuming Zhao, Junhui Hou, Qijian Zhang +2
Geometric analysis fundamentally distinguishes between \textit{extrinsic} and \textit{intrinsic} perspectives. The dominant paradigm in current 3D representation learning relies on…
Joint Geometry-Appearance Human Reconstruction in a Unified Latent Space via Bridge Diffusion
Yingzhi Tang, Qijian Zhang, Junhui Hou
Achieving consistent and high-fidelity geometry and appearance reconstruction of 3D digital humans from a single RGB image is inherently a challenging task. Existing studies typica…
HuGDiffusion: Generalizable Single-Image Human Rendering via 3D Gaussian Diffusion
Yingzhi Tang, Qijian Zhang, Junhui Hou
We present HuGDiffusion, a generalizable 3D Gaussian splatting (3DGS) learning pipeline to achieve novel view synthesis (NVS) of human characters from single-view input images. Exi…
Voronoi-Assisted Diffusion for Computing Unsigned Distance Fields from Unoriented Points
Jiayi Kong, Chen Zong, Junkai Deng +6
Unsigned Distance Fields (UDFs) provide a flexible representation for 3D shapes with arbitrary topology, including open and closed surfaces, orientable and non-orientable geometrie…
A Lightweight UDF Learning Framework for 3D Reconstruction Based on Local Shape Functions
Jiangbei Hu, Yanggeng Li, Fei Hou +5
Unsigned distance fields (UDFs) provide a versatile framework for representing a diverse array of 3D shapes, encompassing both watertight and non-watertight geometries. Traditional…