OpenMMLab's next-generation platform for general 3D object detection.
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Updated
Jul 10, 2024 - Python
A point cloud is a set of data points in space. The points represent a 3D shape or object. Each point has its set of X, Y and Z coordinates.
OpenMMLab's next-generation platform for general 3D object detection.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Frustum PointNets for 3D Object Detection from RGB-D Data
Pytorch framework for doing deep learning on point clouds.
Deep Hough Voting for 3D Object Detection in Point Clouds
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PyTorch implementation of Pointnet2/Pointnet++
World's first general purpose 3D object detection codebse.
Papers and Datasets about Point Cloud.
Convert KITTI dataset to ROS bag file the easy way!
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)