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3d-machine-learning

A resource repository for 3D machine learning

3dssd

3DSSD: Point-based 3D Single Stage Object Detector (CVPR 2020)

badet

Rui Qian, Xin Lai, Xirong Li: BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition 2022)

deep-learning-project-template

A best practice for deep learning project template architecture.

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

fcn.pytorch

helloworld

terrific

lbmnet

A Road Area Detection Using Local Boundary Mask-based Deep Neural Network

lidar-object-clustering-and-ground-remove

激光雷达障碍物检测和聚类，参考论文： Efficient Online Segmentation for Sparse 3D Laser Scans ; 其中包含地面分割代码 ransac;

lidar2rosbag_kitti

A simple way to convert KITTI LiDAR data to rosbag.

lidar_ground_plane_and_obstacles_detections

Python and C++ examples that show shows how to process 3-D Lidar data by segmenting the ground plane and finding obstacles.

lidarobstacledetection

Lidar Obstacle Detection

lidarroadboundarydetection

An speed and accuracy tradeoff method for LiDAR-based road boundary detection method in structured environments

mlcvnet

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

object-detection-in-point-cloud-pole-lane-marking-road-boundary

object-detection-in-point-cloud-road-boundary

Object detection in Point Cloud is popular in HD Map and sensor-based autonomous driving. There basically four types of object you can obtain in daily scenario: road surface - contains painted lane marking and pavement area, support facility - contains road boundary (guardrail and curb), road sign, light pole, etc., uncorrelated object - for example, sidewalk, building, etc., and moving object - such like pedestrian, vehicle, bicycle, etc. In this project, please search references, design and prototype your road boundary (guardrail) detection algorithm.

openpcdet

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

patchwork-plusplus

Patchwork++: Fast and robust ground segmentation method for 3D point cloud. @ IROS'22

pcl-notes

pcl learning notes

point-gnn

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud, CVPR 2020.

pointnet.pytorch

pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

pointnet_pointnet2_pytorch

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

pytorch-fcn

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

road-boundary-detection-based-on-lidar

This algorithm is based on Velodye HDL 64E

road-boundary-edge-curb-detection

ros-academy-for-beginners

**大学MOOC《机器人操作系统入门》课程代码示例

sa-ssd

sarosperceptionkitti

ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite

second.pytorch

PointPillars for KITTI object detection

urban_road_filter

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗