| facebookresearch/pytorch3d |
8,011 |
|
0 |
11 |
about 2 years ago |
14 |
April 28, 2022 |
245 |
other |
Python |
| PyTorch3D is FAIR's library of reusable components for deep learning with 3D data |
| ranahanocka/point2mesh |
408 |
|
0 |
0 |
over 5 years ago |
0 |
|
8 |
mit |
Python |
| Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020] |
| iMoonLab/MeshNet |
316 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
mit |
Python |
| MeshNet: Mesh Neural Network for 3D Shape Representation (AAAI 2019) |
| ThibaultGROUEIX/3D-CODED |
280 |
|
0 |
0 |
over 4 years ago |
0 |
|
4 |
|
Python |
| Pytorch Implementation for the project : `3D-CODED` and `Learning Elementary Structure` |
| suhangpro/mvcnn |
254 |
|
0 |
0 |
over 7 years ago |
0 |
|
12 |
mit |
MATLAB |
| Multi-view CNN (MVCNN) for shape recognition |
| yiyiliao/deep_marching_cubes |
228 |
|
0 |
0 |
about 3 years ago |
0 |
|
5 |
|
Python |
| Code for "Deep Marching Cubes: Learning Explicit Surface Representations", CVPR 2018 |
| NikolaZubic/2dimageto3dmodel |
190 |
|
0 |
0 |
over 3 years ago |
0 |
|
5 |
|
Python |
| We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time. |
| syinari0123/tridepth |
74 |
|
0 |
0 |
about 4 years ago |
0 |
|
3 |
mit |
Python |
| TriDepth: Triangular Patch-based Deep Depth Prediction [Kaneko+, ICCVW2019(oral)] |
| deng-cy/deep_learning_topology_opt |
72 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
MATLAB |
| Code for paper "Self-Directed Online Machine Learning for Topology Optimization" |
| maxjiang93/DDSL |
45 |
|
0 |
0 |
about 5 years ago |
0 |
|
5 |
|
Python |
| DDSL: Deep Differential Simplex Layer for Neural Networks |
