| timzhang642/3D-Machine-Learning |
8,647 |
|
0 |
0 |
about 3 years ago |
0 |
|
19 |
|
|
| A resource repository for 3D machine learning |
| ranahanocka/point2mesh |
408 |
|
0 |
0 |
over 5 years ago |
0 |
|
8 |
mit |
Python |
| Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020] |
| taivop/awesome-data-annotation |
398 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
|
|
| A list of tools for annotating data, managing annotations, etc. |
| lijx10/SO-Net |
296 |
|
0 |
0 |
about 5 years ago |
0 |
|
7 |
mit |
Python |
| SO-Net: Self-Organizing Network for Point Cloud Analysis, CVPR2018 |
| subeeshvasu/Awsome_Deep_Geometry_Learning |
181 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
|
| A list of resources about deep learning solutions on 3D shape processing |
| yanx27/JS3C-Net |
93 |
|
0 |
0 |
over 4 years ago |
0 |
|
2 |
mit |
C++ |
| Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion (AAAI 2021) |
| ericyi/GSPN |
61 |
|
0 |
0 |
almost 7 years ago |
0 |
|
3 |
mit |
Python |
| GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud |
| czq142857/IM-NET |
46 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
other |
Python |
| The improved code for paper "Learning Implicit Fields for Generative Shape Modeling". |
| Frank-ZY-Dou/Coverage_Axis |
41 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
|
MATLAB |
| Official code for the paper Coverage Axis: Inner Point Selection for 3D Shape Skeletonization, Eurographics 2022. |
| bmlklwx/EMS-superquadric_fitting |
28 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
|
MATLAB |
| [CVPR 2022 Oral] Robust and Accurate Superquadric Recovery: a Probabilistic Approach |
