261 Open source projects that are alternatives of or similar to 3DGNN

Fast Plane Extraction Using Agglomerative Hierarchical Clustering (AHC)

A lean C++ library for working with point cloud data

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

3D Graph Neural Networks for RGBD Semantic Segmentation

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

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

Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features

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

L-CAS 3D Point Cloud Annotation Tool

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)

FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)

The open source mesh processing system

Python bindings for the Point Cloud Library (PCL)

[CVPR 2021] Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis (official pytorch implementation)

The PyTorch Implementation of F-ConvNet for 3D Object Detection

A uniform library wrapper for input from V4L2,Freenect,OpenNI,OpenNI2,DepthSense,Intel Realsense,OpenGL simulations and other types of video and depth input..

orb-slam2 with semantic label

A paper list of RGBD semantic segmentation (processing)

A hackable lidar viewer

Efficient 3D Deep Learning

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

Code for PCN: Point Completion Network in 3DV'18 (Oral)

Point cloud semantic segmentation via Deep 3D Convolutional Neural Network

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

Experiments on unsupervised point cloud reconstruction.

Robotics with GPU computing

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

The public CGAL repository, see the README below

Julia bindings for the displaz lidar viewer

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation

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

All those partitioned RGB-D Saliency Datasets we collected are shared in ready-to-use manner.

Implementation of the Point Transformer layer, in Pytorch

our code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification'

[CVPR 2021] Scan2Cap: Context-aware Dense Captioning in RGB-D Scans

Papers and Datasets about Point Cloud.

Python ROS depth estimation from RGB image based on code from the paper "High Quality Monocular Depth Estimation via Transfer Learning"

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

all the meta data needed for nyuv2

Research platform for 3D object detection in PyTorch.

Code for ECCV 2020 "DVI: Depth Guided Video Inpainting for Autonomous Driving"

Differentiable Surface Splatting

[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

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

No description or website provided.

Paperlist of awesome 3D detection methods

Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019

Python binding of 3D visualization library Pangolin

A ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. Izzat and N. Papanikolopoulos, 2017. Distinguish between road and non-road points. Road surface extraction. Plane fit ground filter

Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)

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

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

Neural Point-Based Graphics

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018

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.

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

EU funded Horizon 2020 project