Zhang W's repositories
pointcloud-from-bag-to-frame
Extract and save the point cloud data from rosbag to bin or pcd files!
100-Days-Of-ML-Code
100-Days-Of-ML-Code中文版
AB3DMOT
Official Python Implementation for "A Baseline for 3D Multi-Object Tracking", In Submission
adaptive_clustering
A lightweight and accurate point cloud clustering method
awesome-autonomous-vehicles
Curated List of Self-Driving Cars and Autonomous Vehicles Resources
CodingInterviewChinese2
《剑指Offer》第二版源代码
deepgaze
Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.
GithubSpeedUp
This can help make Github website become speed up
grid_map
Universal grid map library for mobile robotic mapping
ip_basic
Image Processing for Basic Depth Completion
JRMOT_ROS
Source code for JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset
KPConv
Kernel Point Convolutions
LDLS
LDLS (Label Diffusion LiDAR Segmentation) algorithm for instance segmentation of LiDAR point clouds.
learnopencv
Learn OpenCV : C++ and Python Examples
lidar-bonnetal
Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving
lidar_camera_calibration
LiDAR Camera Calibration Based on ROS and MATLAB
multiple-object-tracking-lidar
C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
opencv_tutorials
Opencv4.0 with python (English&中文)， and will keep the update ! 👊
PolarSeg
Implementation for PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation (CVPR 2020)
PythonRobotics
Python sample codes for robotics algorithms.
RandLA-Net
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral)
SARosPerceptionKitti
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
semantic-kitti-api
SemanticKITTI API for visualizing dataset, processing data, and evaluating results.
SJTUThesis
上海交通大学 XeLaTeX 学位论文及课程论文模板
Sparse-Depth-Completion
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. Ranked 1st place on KITTI. (MVA 2019 Conference)