| Fangyh09/pytorch-receptive-field |
323 |
|
0 |
0 |
over 2 years ago |
0 |
|
4 |
apache-2.0 |
Python |
| Compute CNN receptive field size in pytorch in one line |
| 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 |
| skanti/Scan2CAD |
203 |
|
0 |
0 |
over 5 years ago |
0 |
|
5 |
other |
C++ |
| [CVPR'19] Dataset and code used in the research project Scan2CAD: Learning CAD Model Alignment in RGB-D Scans |
| anilbas/3DMMasSTN |
194 |
|
0 |
0 |
about 8 years ago |
0 |
|
5 |
apache-2.0 |
Matlab |
| MatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN) |
| Neerajj9/Text-Detection-using-Yolo-Algorithm-in-keras-tensorflow |
122 |
|
0 |
0 |
about 3 years ago |
0 |
|
6 |
mit |
Jupyter Notebook |
| Implemented the YOLO algorithm for scene text detection in keras-tensorflow (No object detection API used) The code can be tweaked to train for a different object detection task using YOLO. |
| cgtuebingen/Flex-Convolution |
93 |
|
0 |
0 |
almost 7 years ago |
0 |
|
2 |
apache-2.0 |
C++ |
| Source code for: Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds), accepted at ACCV 2018 |
| subodh-malgonde/vehicle-detection |
64 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Detect vehicles in a video |
| tobiagru/Deep-3D-Obj-Recognition |
62 |
|
0 |
0 |
almost 10 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| 3D Object Recognition with Deep Networks Project for 3D Vision - ETHZ |
| DVLP-CMATERJU/RectiNet |
42 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
gpl-3.0 |
Python |
| A Gated and Bifurcated Stacked U-Net Module for Document Image Dewarping |
| davist11/nested-responsive-grid |
42 |
|
0 |
0 |
almost 14 years ago |
0 |
|
0 |
|
Ruby |
| Generate a responsive grid that maintains it’s column sizes two levels deep. |
