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Point Cloud classification,CRF,ML

--1

针对点云中的路杆进行标定

-pcl-

《点云PCL从入门到精通》示例代码

100-days-of-ml-code

100-Days-Of-ML-Code中文版

2-means-simplification

2-Means Simplification for Point Cloud

2018-ccf-bdci-alibaba-3dpoint-cloud-segmentation

2018 CCF大数据与计算智能大赛自动驾驶三维点云分割复赛第四方案

2018-ccf-bdci-alibaba-3dpoint-cloud-segmentation-1

2018 CCF大数据与计算智能大赛自动驾驶三维点云分割复赛第十方案

2019-pr-sparse-multi-view-clustering

The code of SMVSC

2019dfs

IEEE Data Fusion Contest Single-view Semantic 3D Challenge Codes

2d-3d-point-set-registration-based-on-global-rotation-search

# 2D-3D Point Set Registration Based on Global Rotation Search # Copyright (C) 2018 Yinlong [email protected] # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # Any publications resulting from the use of this code should cite the # following paper: # Yinlong Liu, Yuan Dong, Zhijian Song and Manning Wang, "2D 3D Point Set Registration Based on Global Rotation_Search", IEEE Transactions on Image Processing (TIP) # # #==================Note================= # #1. First step->open demo_rot.m. It is a demo of Rotation Search in SO(3) for 2D-3D point set registration. # #2. The input data is set to a real circumstance that 3D point set is far away for projection plane, and in front of camera. Our method also can be applied to unusual condition that camera is surrounded by 3D point set, only if you make some fix. # #3. RotaionSearch.m is the kernel of algorithm. You can easily extend it to SE(3) searching by grid-search, while tuning parameters depends on your tasks. # #4. Fast and Global 2D-3D point set registration without correspondence is still an open problem and need further explorations. I am very happy that if you could benefit from our code. # # # Author: Yinlong Liu # Date: 20181218 # Revision: 1.0

2d-3d-registration

Code for ICRA 2016 Paper "2D-Image to 3D-Range Registration in Urban Environments via Scene Categorization and Combination of Similarity Measurements"

2s-agcn

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

38-cloud-a-cloud-segmentation-dataset

This data set includes Landsat 8 images and their manually extracted pixel-level ground truths for cloud detection.

3d

Pipeline for point cloud to 3D object creation.

3d-aae

Adversarial Autoencoders for Compact Representations of 3D Point Clouds

3d-adv-pc

Generating 3D Adversarial Point Clouds

3d-algorithms---segmenting-point-clouds

Given a 3D point cloud, we assign different planar surfaces different colors. First project for my Advanced 3D algorithms grad class at the CUNY Graduate Center.

3d-bat

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

3d-bonet

3D-BoNet in Tensorflow (preprint arXiv: 1906.01140)

3d-boundingbox

PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry

3d-box-estimation-of-vehicles-from-aerial-lidar-point-clouds

Using LIBLAS we find the estimate positions of vehicle from Aerial LIDAR scans mounted on a Drone flying over the top of the road. The idea is not based on 3D CNNs, but it is rather based on trimming the 3D search space by excluding any set of point cloud that does not belong to the road, then downsampling of PC using 3D Voxelization and move a 3D fix-sized box (at the beginning) and search the ones that have the highest occupancy.

3d-building-reconstruction

3d-coded

Pytorch Implementation for the project : 3D-CODED : 3D Correspondences by Deep Deformation"

3d-convolutional-neural-networks-with-lidar

Implementations of popular CNNs in 3D for developing forest inventories from LiDAR

3d-cutter

Cut a tetrahedral mesh with a triangle mesh in 3D.

3d-cyclegans

Reconstruction from sparse 3D models to dense 3D models by CycleGANs and extra autoencoder training.

3d-deep-learning-paper-list

3d-deepbox

3D Bounding Box Estimation Using Deep Learning and Geometry (MultiBin)

3d-fcr-alphagan

Fully Convolutional Refined Auto Encoding Generative Adversarial Networks for 3D Multi Object Scenes

3d-gan

Use of this model for generating 3d shapes and also 3d reconstruction from images