259 Open source projects that are alternatives of or similar to Samplenet

A learned sampling approach for point clouds (CVPR 2019)

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Differentiable Surface Splatting

The public CGAL repository, see the README below

Geometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)

3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.

Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Point cloud semantic segmentation via Deep 3D Convolutional Neural Network

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

🌐 Web demo using the Geometrize Haxe library to recreate images with geometric primitives

A hackable lidar viewer

Python binding of 3D visualization library Pangolin

FPConv: Learning Local Flattening for Point Convolution, CVPR 2020

TriWild: Robust Triangulation with Curve Constraints

A high-performance neural network library for point cloud processing.

CloudCompare main repository

L-CAS 3D Point Cloud Annotation Tool

Code for Pointwise Convolutional Neural Networks, CVPR 2018

Paperlist of awesome 3D detection methods

open Multi-View Stereo reconstruction library

Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)

[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.

An integrated SfM (Structure from Motion) and MVS (Multi-View Stereo) solution.

Polylidar3D - Fast polygon extraction from 3D Data

Automatic conservative mesh occluder generation by box filling

The open source mesh processing system

Neural Point-Based Graphics

This is the official implementation of RSNet.

code/webpage for the DeepMapping project

Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)

Papers and Datasets about Point Cloud.

Patch-base progressive 3D Point Set Upsampling

DBNet: A Large-Scale Dataset for Driving Behavior Learning, CVPR 2018

Lightweight and Accurate Point Cloud Clustering

Implementation of the Point Transformer layer, in Pytorch

Cluster based segmentation of Point Cloud with PCL lib in ROS

Matlab geometry toolbox for 2D/3D geometric computing

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud (ECCV 2018)

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)

Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling （CVPR 2020）

Keras implementation for Pointnet

Research platform for 3D object detection in PyTorch.

A list of resources about deep learning solutions on 3D shape processing

A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'

orb-slam2 with semantic label

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

User-friendly, commercial-grade software for processing aerial imagery. 🛩

Accompanying library for the Record3D iOS app (https://record3d.app/). Allows you to receive RGBD stream from iOS devices with TrueDepth camera(s).

A Laser-Camera Calibration Toolbox extending from that at http://www.cs.cmu.edu/~ranjith/lcct.html

Course material for a grad-level course in Geometry Processing.

[CVPR'19] JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds

📚 The list of vision-based SLAM / Visual Odometry open source, blogs, and papers

DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DOF Relocalization

OptCuts, a new parameterization algorithm, jointly optimizes arbitrary embeddings for seam quality and distortion. OptCuts requires no parameter tuning; automatically generating mappings that minimize seam-lengths while satisfying user-requested distortion bounds.

C++ library and programs for reading and writing ASPRS LAS format with LiDAR data