| open-mmlab/OpenPCDet |
4,100 |
|
0 |
0 |
over 2 years ago |
0 |
|
43 |
apache-2.0 |
Python |
| OpenPCDet Toolbox for LiDAR-based 3D Object Detection. |
| isl-org/Open3D-ML |
2,221 |
|
0 |
0 |
3 months ago |
0 |
|
104 |
other |
Python |
| An extension of Open3D to address 3D Machine Learning tasks |
| mit-han-lab/bevfusion |
1,565 |
|
0 |
0 |
over 2 years ago |
0 |
|
84 |
apache-2.0 |
Python |
| [ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation |
| maudzung/Complex-YOLOv4-Pytorch |
988 |
|
0 |
0 |
over 3 years ago |
0 |
|
43 |
gpl-3.0 |
Python |
| The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds" |
| loicland/superpoint_graph |
691 |
|
0 |
0 |
over 2 years ago |
0 |
|
14 |
mit |
Python |
| Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs |
| mit-han-lab/spvnas |
620 |
|
0 |
0 |
almost 2 years ago |
0 |
|
4 |
mit |
Python |
| [ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution |
| fangchangma/self-supervised-depth-completion |
418 |
|
0 |
0 |
about 5 years ago |
0 |
|
25 |
mit |
Python |
| ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera" |
| 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) |
| jhultman/vision3d |
197 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
mit |
Python |
| Research platform for 3D object detection in PyTorch. |
| Yvanali/Deep-Learning-for-LiDAR-Point-Clouds |
134 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
|
|
| Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review |
