YanpingLi's starred repositories
YOLOP-opencv-dnn
使用OpenCV部署全景驾驶感知网络YOLOP，可同时处理交通目标检测、可驾驶区域分割、车道线检测，三项视觉感知任务，包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行， 从而彻底摆脱对任何深度学习框架的依赖。
awesome-remote-sensing-change-detection
List of datasets, codes, and contests related to remote sensing change detection
techniques
Techniques for deep learning with satellite & aerial imagery
GAOFEN2021_CHANGEDETECTION
第五届中科星图杯高分辨率可见光图像中建筑物普查与变化检测
Point-cloud-registration
点云配准入门知识
nuscenes-devkit
The devkit of the nuScenes dataset.
cascade-rcnn
Caffe implementation of multiple popular object detection frameworks
offline-tileServer
离线瓦片地图。1、多进程/多线程/异步爬取瓦片地图；2、Flask + Leaflet 构建离线地图服务。
FusionLane
The source code of paper FusionLane
map-matching
The map matching functionality is now located in the main repository https://github.com/graphhopper/graphhopper#map-matching
lane-detection
point cloud lane detection
RoadMarkingExtraction
🛣️ automatic extraction of road markings from MLS or ALS point cloud [ISPRS-A' 19]
Lane-Marking-Detection
This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.
awesome-lane-detection
A paper list of lane detection.
3D-PointCloud
Papers and Datasets about Point Cloud.
Pointnet_Pointnet2_pytorch
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
pointnet.pytorch
pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593
awesome-3dcv-papers-daily
主要记录计算机视觉、VSLAM、点云、结构光、机械臂抓取、三维重建、深度学习、自动驾驶等前沿paper与文章。