331 Open source projects that are alternatives of or similar to PointCutMix

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

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

Code for Pointwise Convolutional Neural Networks, CVPR 2018

Tensor2tensor experiment with SpecAugment

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

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

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

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

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

Implementation of the Point Transformer layer, in Pytorch

Keras implementation for Pointnet

An extended TSP (Time Stretched Pulse). CAPRICEP substantially replaces FVN. CAPRICEP enables interactive and real-time measurement of the linear time-invariant, the non-linear time-invariant, and random and time varying responses simultaneously.

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

orb-slam2 with semantic label

This is the official implementation of RSNet.

中文NER的那些事儿

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

Papers and Datasets about Point Cloud.

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

[Medical Image Analysis] Adversarial Data Augmentation with Chained Transformations (AdvChain)

3D Heritage Online Presenter

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

A small Java-based tool for the generation of point cloud visualization datasets according to Cesium 3D Tiles.

Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.

Deep Hough Voting for 3D Object Detection in Point Clouds

Research platform for 3D object detection in PyTorch.

Fast and robust algorithm to extract edges in unorganized point clouds

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)

Pytorch framework for doing deep learning on point clouds.

Differentiable Surface Splatting

Weakly Supervised 3D Object Detection from Point Clouds (VS3D), ACM MM 2020

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

Fast Plane Extraction Using Agglomerative Hierarchical Clustering (AHC)

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

Specification for streaming massive heterogeneous 3D geospatial datasets 🌎

Experiments on unsupervised point cloud reconstruction.

Regularized Graph CNN for Point Cloud Segmentation

Paperlist of awesome 3D detection methods

[CVPR 2021 - Oral] UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering

Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019

Load 3MX/3MXB format LOD model files generated by Bentley ContextCapture into Unity.

Python binding of 3D visualization library Pangolin

Scripts showcasing filtering techniques applied to point cloud data.

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

3D LIDAR-based Graph SLAM

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

PyTorch implementation of Pointnet2/Pointnet++

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

Learning Graph-Convolutional Representations for Point Cloud Denoising (ECCV 2020)

Neural Point-Based Graphics

Point cloud importer & renderer for Unity

Julia bindings for the displaz lidar viewer

Grid-GCN for Fast and Scalable Point Cloud Learning

code/webpage for the DeepMapping project

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

Efficient 3D Deep Learning

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

Image rotation and cropping out the black borders in TensorFlow