Python Surface-reconstruction Resources

geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On

Welcome to the lidar package lidar is Python package for delineating the nested hierarchy of surface depressions in digital elevation models (DEMs). I

RfD-Net [Project Page] [Paper] [Video] RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction Yinyu Nie, Ji Hou, Xiaoguang Han, Matthi

CoReNet CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image. It produces coherent reconstructions, where all objec

NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video Project Page | Paper NeuralRecon: Real-Time Coherent 3D Reconstruction from Mon

PyMAF This repository contains the code for the following paper: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop Hongwe

Poisson Surface Reconstruction for LiDAR Odometry and Mapping Surfels TSDF Our Approach Table: Qualitative comparison between the different mapping te

A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous

DeepMLS: Deep Implicit Moving Least-Squares Functions for 3D Reconstruction This repository contains the implementation of the paper: Deep Implicit Mo

Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction Code for the ECCV 2020 paper by Yiming Qian and Yasutaka Furukawa Getting

InVesalius InVesalius generates 3D medical imaging reconstructions based on a sequence of 2D DICOM files acquired with CT or MRI equipments. InVesaliu

Meshroom is a free, open-source 3D Reconstruction Software based on the AliceVision Photogrammetric Computer Vision framework. Learn more details abou

Non-Rigid Neural Radiance Fields This is the official repository for the project "Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synt

✨ Linty Fresh ✨ Keep your codebase sparkly clean with the power of LINT! Linty Fresh parses lint errors and report them back to GitHub as comments on

AIST++ API This repo contains starter code for using the AIST++ dataset. To download the dataset or explore details of this dataset, please go to our

Stable Head Pose Estimation and Landmark Regression via 3D Dense Face Reconstruction Reimplementation of (ECCV 2020) Towards Fast, Accurate and Stable