There are 3 repositories under pointclouds topic.
🔥[IEEE TPAMI 2020] Deep Learning for 3D Point Clouds: A Survey
The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.
A no dependency, header-only, license free, fast supervoxel segmentation library for 3D point clouds
Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020)
Visualize Data From Stray Scanner https://keke.dev/blog/2021/03/10/Stray-Scanner.html
New Blender 3.0* / 3.1 PLY importer v2.0 for point clouds and nonstandard models.
We propose a framework that accurately derives the 3D tongue shape from single images. A high detailed 3D point cloud of the tongue surface and a full head topology along with the tongue expression can be estimated from the image domain.
Preprocessing, coordinate frame calibration, configuration files, and launching procedure used to generate point clouds with Google Cartographer for the RadMAP acquisition system. The RadMAP acquisition system consists of two LIDARS, differential GPS, two Ladybug 360 cameras, and an IMU.
[WACV 2021] Dynamic Plane Convolutional Occupancy Networks
Using Euclidiean Clustering and RANSAC to detect Objects in Lidar captured Point Clouds (PCDs)
Delft University of Technology MSc. Geomatics Synthesis (GEO1101) Project 5: 3D Representations for Visual Insight
Fast 3D point cloud processing lib based on C++/cuda
Simple PCL bindings for Python and other utilities for processing point clouds.
Tree detection project for Rijkswaterstaat, carried out by the Spinlab (Vrije Universiteit Amsterdam)
Time to collision estimation Using YoloV3 and Projecting Lidar point clouds to 2d image for vehicle tracking
A DIY-box containing 2 Raspberry Pi cameras connected to a Raspberry Pi 3 to capture multiple stereo images and reconstruct a 3d pointcloud.
Code for the Didi/Udacity SDC Challenge 2017
3ِD Change Detection In Point Cloud
A quick and easy kinect-to-pointcloud converter for MacOS/Swift/Cocoa.
Research notebooks on CV automation techniques
Final project for the Computational Intelligence and Deep Learning course at University of Pisa.
The "Knowledge-based object Detection in Image and Point cloud" (KnowDIP) project aims at the conception of a framework for automatic object detection in unstructured and heterogeneous data. This framework uses a representation of human knowledge in order to improve the flexibility, accuracy, and efficiency of data processing.
Read point cloud's (LAS/LAZ) header in browser and node.js
A table top pointcloud segmentation using ROS
Repo for robotics algorithms implemented in C++
Scripts and Utilities for Agisoft Metashape
Time to collision based on lidar and camera data.
Code for Self-Supervised Few-Shot Learning on Point Clouds paper at NeurIPS 2020
Rui Qian, Xin Lai, Xirong Li: 3D Object Detection for Autonomous Driving: A Survey (Pattern Recognition 2022: IF=7.740)