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

Code examples of point cloud processing in python.

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

Code for rendering images for NeurRIPS 2020 paper "Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D"

These scripts are part of the project 3D-EdgeAngle – A semi-automated 3D digital method to systematically quantify stone tool edge angle and design.

Keras Implementation of paper "Combining Residual Networks with LSTMs for Lipreading", final project of course: Israel Deep Learning Course, with grant from Google