FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)
[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Code for PCN: Point Completion Network in 3DV'18 (Oral)
Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019
Robotics with GPU computing
Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018
The public CGAL repository, see the README below
Python bindings for the Point Cloud Library (PCL)
Differentiable Point Cloud Sampling (CVPR 2020 Oral)
C++ library and programs for reading and writing ASPRS LAS format with LiDAR data
The PyTorch Implementation of F-ConvNet for 3D Object Detection
3D Graph Neural Networks for RGBD Semantic Segmentation
3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling
Research platform for 3D object detection in PyTorch.
The open source mesh processing system
Differentiable Surface Splatting
A high-performance neural network library for point cloud processing.
DBNet: A Large-Scale Dataset for Driving Behavior Learning, CVPR 2018
Point cloud semantic segmentation via Deep 3D Convolutional Neural Network
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Python binding of 3D visualization library Pangolin
PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling （CVPR 2020）
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
Extrinsic lidar camera calibration
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
Grid-GCN for Fast and Scalable Point Cloud Learning
Lidar camera calibration
Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
Patch-base progressive 3D Point Set Upsampling
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
Code for Pointwise Convolutional Neural Networks, CVPR 2018
Yolo3d Yolov4 Pytorch
YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud (ECCV 2018)
open Multi-View Stereo reconstruction library
Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
FPConv: Learning Local Flattening for Point Convolution, CVPR 2020
Awesome Robotic Tooling
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.
Polylidar3D - Fast polygon extraction from 3D Data
Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'
This is the official implementation of RSNet.