Stars
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
Learning Continuous Signed Distance Functions for Shape Representation
Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020]
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
A lightweight tool for labeling 3D bounding boxes in point clouds.
Official code for "Boundary loss for highly unbalanced segmentation", runner-up for best paper award at MIDL 2019. Extended version in MedIA, volume 67, January 2021.
Morphological snakes for image segmentation and tracking
Pure Numpy Implementation of the Coherent Point Drift Algorithm
NI-DAQmx API for Python, created and supported by NI
Learning Implicit Surfaces from Point Clouds (ECCV 2020)
How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study
[ECCV 2024] Official implementation of the paper "GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views"
GPU Accelerated Non-rigid ICP for surface registration
Point2Skeleton: Learning Skeletal Representations from Point Clouds (CVPR2021)
Implementation of ICML'2021:Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
[ICML'23 Oral] Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping
🔄 [ECCV‘24] Pytorch implementation of 'Surface Reconstruction from 3D Gaussian Splatting via Local Structural Hints'
A deep-learning approach for direct whole-heart mesh reconstruction
Modified version of non-rigid Iterative closest point algorithm for fitting to noisy point clouds
This repository is an implementation of non rigid icp
Implementation of ICML'2021:Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces