Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
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Updated
Mar 24, 2023 - Python
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Repository for automatic classification and labeling of Urban PointClouds using data fusion and region growing techniques.
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
Procedural 3D data generation pipeline for architecture
[MICCAI'2020 PRIME] Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Severity Estimation.
Code examples of point cloud processing in python.
An interactive 3D web viewer of up to million points on one screen that represent data. Provides interaction for viewing high-dimensional data that has been previously embedded in 3D or 2D. Based on graphosaurus.js and three.js. For a Linux release of a complete embedding+visualization pipeline please visit https://github.com/sonjageorgievska/Em…
Examples of point cloud processing in python
An easy-to-use wrapper around some of Open3D's registration functionality.
Dataset Generation Code for CVPR 2022 Paper Primtive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives
This repository contains methods for the automatic extraction of urban street furniture from labeled PointClouds.
Point Cloud Augmentation
In this repository you are going to find the documents we produced to support the discussion in our Digital Methods of the Month. These documents will help you orienting yourself if you want to pickup the method in your research. Go to the readme file
Code for rendering images for NeurRIPS 2020 paper "Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D"
Assignment solutions for the Machine Learning for 3D Geometry (ML43D) course at TUM
These scripts are part of the project 3D-EdgeAngle – A semi-automated 3D digital method to systematically quantify stone tool edge angle and design.
Implementation of NeRF paper
Tool for 3D data processing using AT's 3D sensors
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