| loicland/superpoint_graph |
691 |
|
0 |
0 |
over 2 years ago |
0 |
|
14 |
mit |
Python |
| Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs |
| wvangansbeke/Sparse-Depth-Completion |
372 |
|
0 |
0 |
almost 4 years ago |
0 |
|
1 |
other |
Python |
| Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) |
| MankaranSingh/Auto-Depth |
64 |
|
0 |
0 |
about 4 years ago |
0 |
|
3 |
|
Python |
| 3D Reconstruction / Pseudo LiDAR via Deep Learning |
| weecology/NeonTreeEvaluation |
59 |
|
0 |
0 |
about 4 years ago |
0 |
|
1 |
cc0-1.0 |
Python |
| Benchmark dataset for tree detection for airborne RGB, Hyperspectral and LIDAR imagery |
| weecology/DeepLidar |
48 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
|
Python |
| LIDAR and RGB Deep Learning Model for Individual Tree Segmentation |
| ShreyasSkandanS/DFuseNet |
47 |
|
0 |
0 |
over 6 years ago |
0 |
|
1 |
gpl-3.0 |
Python |
| ITSC 2019 | This is the accompanying code repository for our paper "DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion" | PyTorch, Python 3 |
| anshulpaigwar/Frustum-Pointpillars |
17 |
|
0 |
0 |
over 3 years ago |
0 |
|
4 |
mit |
Python |
| Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR |
| VitoRazor/Lidar_RGB_detector |
14 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
mit |
Python |
| zcbmlijygrdwa/camera_lidar_fusion |
12 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
|
Python |
| Calibrate camera to lidar |
| cyshih704/DeepLiDAR |
11 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
|
Python |
