Mattia D'Urso

I am a PhD student in Prof. Friedrich Fraundorfer's group at the Institute for Visual Computing (IVC) at Graz University of Technology, Austria.

Previously, I gained professional experience at the Canva office in Vienna and at Infineon Technologies in Villach, Austria.

I hold a joint Master's double degree from the University of Klagenfurt and the University of Udine, where I also completed my Bachelor's degree.

Email  /  Scholar  /  Github  /  LinkedIn

Research

My research focuses on 3D Computer Vision and Machine Learning, with a specific interest in Pose Estimation and Structure from Motion (SfM).

TerraSky3D is a high-resolution 4K dataset of European landmarks comprising over 50,000 images across 150 scenes, specifically designed to bridge the modality gap between ground-level and aerial perspectives for 3D reconstruction. It provides curated camera poses and dense depth maps.
Code and data are available here.

A LoD of Gaussians enables the reconstruction and interactive visualization of ultra-large-scale scenes by replacing traditional scene partitioning with a dynamic, out-of-core Level-of-Detail framework.

SANDesc is a descriptor module that can be trained on top of any existing keypoint detector. It significantly improves pose estimation performances on high-resolution images.
Code is available here. Webpage is available here.

PyTorchGeoNodes is a differentiable module that enables reconstruction of 3D objects and their semantic parameters using interpretable shape programs.
Code is available here.

Template adapted from Jon Barron.