1440 Open source projects that are alternatives of or similar to Superpoint_graph

🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.

WaSR Segmentation Network for Unmanned Surface Vehicles v0.5

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

Pytorch code for semantic segmentation using ERFNet

Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

BCDU-Net : Medical Image Segmentation

Python bindings for the Point Cloud Library (PCL)

Julia bindings for the displaz lidar viewer

Code and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".

🔥🔥Official Repository for Multi-Human-Parsing (MHP)🔥🔥

HyperSeg - Official PyTorch Implementation

A PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network(PyTorch >= 1.4)

Inference script and frozen inference graph with fine tuned weights for semantic segmentation on images from the KITTI dataset.

Papers and Datasets about Point Cloud.

3D Graph Neural Networks for RGBD Semantic Segmentation

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

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

Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform (RA-L)

LiDAR fog simulation

A python tool for fitting primitives 3D shapes in point clouds using RANSAC algorithm

TF2 implementation of PointNet for segmenting point clouds

Binary semantic segmentation with UNet based on MobileNetV2 encoder

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.

Summary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video.

Semantic Segmentation PyTorch code for our paper: Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

A clean PointNet++ segmentation model implementation. Support batch of samples with different number of points.

A hackable lidar viewer

Research platform for 3D object detection in PyTorch.

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

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

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019

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

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

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021 Oral)

Cut and paste augmentation for object detection and instance segmentation

Official version of 'Weakly Supervised 3D object detection from Lidar Point Cloud'(ECCV2020)

[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

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

Pytorch framework for doing deep learning on point clouds.

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

segmentation paper reading notes

EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

exudates detection using hybrid approach (Image Morphology & Machine Learning)

Behind the Curtain: Learning Occluded Shapes for 3D Object Detection

Machine Learning Project to identify an ID Card on an image

KITTI data processing and 3D CNN for Vehicle Detection

An extension of Open3D to address 3D Machine Learning tasks

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.

Segmentation models with pretrained backbones. PyTorch.

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

Grid-GCN for Fast and Scalable Point Cloud Learning

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.

Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network

A pointnet++ fork, with focus on semantic segmentation of differents datasets