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University of Bonn
- https://paulroetzer.github.io
Stars
CVPR 2024, Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching
A library of geometry processing tools for computer graphics
A Jekyll version of the "Massively" theme by HTML5 UP.
PIPS-IPM++ - a massively parallel interior point method for primal-dual block angular Linear Programms
Lightweight Python framework that provides a high-level API for creating and rendering scenes with Blender.
Optimum cycle mean algorithms: Efficient implementations as used in my research papers.
Rotation-Invariant Transformer for Point Cloud Matching
Refine high-quality datasets and visual AI models
This repository implements the remeshing algorithm presented in ReMatching: Low-Resolution Representations for Scalable Shape Correspondence.
PyTorch common framework to accelerate network implementation, training and validation
Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features [CVPR 2024]
Stanford LaTeX poster template
Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis
Implementation of the paper "Surface Map Homology Inference"
Demo code for the paper "Discrete Optimization for Shape Matching"
Accompanying code for "An Elastic Basis for Spectral Shape Correspondence"
Surface Simplification using Intrinsic Error Metrics
Implementation of our paper "Polygon Laplacian Made Simple", Eurographics 2020.
SIGGRAPH23: Unsupervised Learning of Robust Spectral Shape Matching
Pytorch implementation of DiffusionNet for fast and robust learning on 3D surfaces like meshes or point clouds.
OptCuts, a new parameterization algorithm, jointly optimizes arbitrary embeddings for seam quality and distortion. OptCuts requires no parameter tuning; automatically generating mappings that minim…
An unofficial implementation of Seamless Surface Mappings (Aigerman et al., SIGGRAPH 2015)
Implementation of "Large Steps in Inverse Rendering of Geometry"