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3d-pointcloud

Papers and Datasets about Point Cloud.

adqsm

AdQSM is a new tree quantitative structure model (QSM) that can reconstruct the 3D branch geometry of individual tree from Terrestrial Laser Scanning (TLS) point clouds. Many attributes of the trunk or branch can also be quantitatively calculated (as shown in the table below). For example, tree volume (trunk and branch), DBH and tree height parameters can be extracted directly. It allows point clouds collected by different sensors to serve as input point clouds. In addition to TLS, UAV LiDAR, mobile LiDAR, SLAM and even photogrammetry are also included under the premise of appropriate point cloud density.

codeformer

[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

codethesistropicalforests

An overview of the most important codes of my master dissertation. It includes an algorithm to derive DBH from TLS point cloud data of individual trees and structural features.

daylength

deepforest

Python Package for Tree Crown Detection in Airborne RGB imagery

demo---practical-optimal-registration-of-terrestrial-lidar-scan-pairs

depthfusion

Fuse multiple depth frames into a point cloud

detectree2

Python package for automatic tree crown delineation based on the Detectron2 implementation of Mask R-CNN

forestmetrics

Individual tree segmentation from LiDAR-derived point clouds

fsct

globalmatch

GlobalMatch: Registration of forest terrestrial point clouds by global matching of relative stem positions [ISPRS 2023]

gray-level-cooccurrence-matrix

Gray Level Co-occurrence Matrix (GLCM) with python library

imagej

itsme

las2pcd

Convert .LAS point cloud to PCL-compatible .PCD format

lastools

efficient tools for LiDAR processing

lidar_plot_registration

3D visualization of forest inventory plots and probabilistic approach to co-registering a stem map with lidar data

lidarseg

pangu-weather-readytogo

Unofficial demonstration of Huawei's Pangu Weather Model. Implementing the entire process of data preparation for input, forecasting conversion of forecasted results, and visualization.

pct

Jittor implementation of PCT:Point Cloud Transformer

pointcloudsvmdemo

三维点云激光分类（建筑，树木）

pointsift

a module for 3D semantic segmentation in point clouds.

pycrown

PyCrown - Fast raster-based individual tree segmentation for LiDAR data

pycv

用于巩固数字图像处理的Python程序

qsm-fanni-matlab

Quantitative structure models - Foliage and needles naive insertion algorithm MATLAB implementation.

sentinel-tree-cover

Image segmentations of trees outside forest

source

Source code of the TLSeparation Python package.

stablediffusion

High-Resolution Image Synthesis with Latent Diffusion Models

tlstools

Collate and visualise treeseg, optqsm and nallom outputs