5 papers
SeamFlow: Structure-Aware Flow Matching on Edge Probabilities for Artist-Like UV Unwrapping
Yuming Zhao, Zangyueyang Xian, Qijian Zhang +4
3D surface cutting and UV unwrapping are fundamental problems in computer graphics. Traditional geometric optimization methods mainly focus on reducing parameterization distortion,…
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…
FlexPara: Flexible Neural Surface Parameterization
Yuming Zhao, Qijian Zhang, Junhui Hou +3
Surface parameterization is a fundamental geometry processing task, laying the foundations for the visual presentation of 3D assets and numerous downstream shape analysis scenarios…
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…
Flatten Anything: Unsupervised Neural Surface Parameterization
Qijian Zhang, Junhui Hou, Wenping Wang +1
Surface parameterization plays an essential role in numerous computer graphics and geometry processing applications. Traditional parameterization approaches are designed for high-q…