2 citations · 3 across the 11 of their papers we have counts for
12 papers
Q-MAGIC: Quad-only Mesh Autoregressive Generation via Singularity-Aware Circular Relative Offset Tokenization
Yuming Zhao, Zezeng Li, Weimin Wang +2
Autoregressive models have proven effective for triangular mesh generation by transforming it into predicting the next face, converting the non-differentiable connectivity predicti…
Underwater360: Reconstructing Underwater Scenes from Panoramic Images with Omnidirectional Gaussian Splatting
Jiangbei Hu, Weichao Song, Shibo Yu +8
Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-media effects such as absorptio…
PolycubeNet: A Dual-latent Diffusion Model for Polycube-Based Hexahedral Mesh Generation
Lu He, Qitao Deng, Junjiang Deng +5
Hexahedral meshes are widely used in simulation pipelines, yet automatic generation remains challenging for complex CAD geometries. Polycube-based hexahedral meshing is a represent…
OT-ALD: Aligning Latent Distributions with Optimal Transport for Accelerated Image-to-Image Translation
Zhanpeng Wang, Shuting Cao, Yuhang Lu +3
The Dual Diffusion Implicit Bridge (DDIB) is an emerging image-to-image (I2I) translation method that preserves cycle consistency while achieving strong flexibility. It links two i…
Solving Prior Distribution Mismatch in Diffusion Models via Optimal Transport
Zhanpeng Wang, Shenghao Li, Jiameng Che +4
Diffusion Models (DMs) have achieved remarkable progress in generative modeling. However, the mismatch between the forward terminal distribution and reverse initial distribution in…
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…
DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport
Zezeng Li, ShengHao Li, Zhanpeng Wang +3
Sampling from diffusion probabilistic models (DPMs) can be viewed as a piecewise distribution transformation, which generally requires hundreds or thousands of steps of the inverse…
OT-Net: A Reusable Neural Optimal Transport Solver
Zezeng Li, Shenghao Li, Lianbao Jin +2
With the widespread application of optimal transport (OT), its calculation becomes essential, and various algorithms have emerged. However, the existing methods either have low eff…