2 citations · 3 across the 11 of their papers we have counts for
5 papers · 2 filters
MergeNet: Explicit Mesh Reconstruction from Sparse Point Clouds via Edge Prediction
Weimin Wang, Yingxu Deng, Zezeng Li +2
This paper introduces a novel method for reconstructing meshes from sparse point clouds by predicting edge connection. Existing implicit methods usually produce superior smooth and…
HOTS3D: Hyper-Spherical Optimal Transport for Semantic Alignment of Text-to-3D Generation
Zezeng Li, Weimin Wang, Yuming Zhao +3
Recent CLIP-guided 3D generation methods have achieved promising results but struggle with generating faithful 3D shapes that conform with input text due to the gap between text an…
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…
Point Cloud Compression via Constrained Optimal Transport
Zezeng Li, Weimin Wang, Ziliang Wang +1
This paper presents a novel point cloud compression method COT-PCC by formulating the task as a constrained optimal transport (COT) problem. COT-PCC takes the bitrate of compressed…
Topology-Aware Latent Diffusion for 3D Shape Generation
Jiangbei Hu, Ben Fei, Baixin Xu +6
We introduce a new generative model that combines latent diffusion with persistent homology to create 3D shapes with high diversity, with a special emphasis on their topological ch…