Riccardo de Lutio

Riccardo de Lutio

Senior Research Scientist

Spatial Intelligence Lab, NVIDIA

Biography

I am a Senior Research Scientist at NVIDIA in the Spatial Intelligence Lab, working on 3D vision, neural reconstruction, simulation, and world models.

Prior to NVIDIA, I obtained my PhD at ETH Zurich in the EcoVision Lab, Photogrammetry and Remote Sensing Group under the supervision of Prof. Jan Wegner and Prof. Konrad Schindler. During my PhD I worked on super-resolution, depth upsampling/completion, fine-grained classification, and biodiversity monitoring.

Education
  • PhD in Computer Vision, 2023

    ETHZ

  • MSc in Machine Learning, 2017

    Imperial College London

  • BSc in Physics, 2016

    EPFL

Publications

(2026). ArtiFixer: Enhancing and Extending 3D Reconstruction with Auto-Regressive Diffusion Models. In SIGGRAPH 2026.

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(2026). DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer. In CVPR 2026.

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(2026). SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms. In ICLR 2026.

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(2025). Towards Learning to Complete Anything in Lidar. In ICML 2025.

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(2025). FlorID – a nationwide identification service for plants from photos and habitat information. Environmental Monitoring and Software.

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(2025). OmniRe: Omni Urban Scene Reconstruction. In ICLR (Spotlight).

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(2024). 3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes. In SIGGRAPH Asia.

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(2024). NAFlora-1M: Continental-Scale High-Resolution Fine-Grained Plant Classification Dataset. In DMLR.

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(2024). Multispecies Deep Learning Using Citizen Science Data Produces More Informative Plant Community Models. In Nature Communications.

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(2024). RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting. In arXiv.

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(2022). Learning Graph Regularisation for Guided Super-Resolution. In CVPR.

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(2022). The Herbarium 2021 Half–Earth Challenge Dataset and Machine Learning Competition. In Frontiers in Plant Science.

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(2021). Digital Taxonomist: Identifying Plant Species in Community Scientists' Photographs. In ISPRS.

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(2019). Guided Super-Resolution as Pixel-to-Pixel Transformation. In ICCV.

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Experience

 
 
 
 
 
NVIDIA Spatial Intelligence Lab
Senior Research Scientist
Oct 2023 – Present Santa Clara
Working on 3D vision, neural reconstruction, simulation, and world models in Zan Gojcic’s team, part of Prof. Sanja Fidler’s group.
 
 
 
 
 
NVIDIA Toronto AI Lab
Research Scientist Intern
Jul 2022 – Dec 2022 Zurich
Working in Prof. Sanja Fidler’s team.
 
 
 
 
 
ETHZ
Research Assistant
Oct 2018 – Feb 2023 Zurich
Research Assistant as a PhD student in the EcoVision Lab, Photogrammetry and Remote Sensing Group, supervised by Prof. Jan Dirk Wegner and Prof. Konrad Schindler.
 
 
 
 
 
Machine Learning and Optimization Lab at EPFL
Scientific Assistant
Oct 2017 – Jun 2018 Lausanne

Working on A Machine Learning Platform for Emerging Viral Diseases in Africa (part of SAFIA project) with Prof. Martin Jaggi and Dr. Mary-Anne Hartley

  • Designing an algorithm that helps clinicians better predict the cause of paediatric fever
  • Potentially helps detecting epidemic outbursts
 
 
 
 
 
Argelander-Institut für Astronomie at Bonn University
Research Intern
Jun 2016 – Jul 2016 Bonn

Working on Artificial neural networks handling noisy features with Dr. Malte Tewes

  • Noisy multivariate data, which depend on some physical explanatory parameters
  • Creating a model neural network architecture that finds accurate estimates for parameters

Education

 
 
 
 
 
ETHZ
PhD Computer Vision
Oct 2018 – Jun 2023 Zurich
Ph.D. in the EcoVision Lab, Photogrammetry and Remote Sensing Group, supervised by Prof. Jan Dirk Wegner and Prof. Konrad Schindler.
 
 
 
 
 
Imperial College London
MSc Computing (Machine Learning)
Sep 2016 – Aug 2017 London

First Class Honours. Master Project, F1 Overtaking Model with Mercedes F1 Team and Prof. Marc Deisenroth.

  • Creating a probabilistic model for overtaking during a race, key aspect of race simulation engine.
 
 
 
 
 
Imperial College London
BSc Physics - Exchange Program
Sep 2015 – Jun 2016 London

Bachelor Project, Machine Learning and Galaxy Surveys with Dr. David Clements.

  • Finding clusters in an unsupervised way and comparing them with the astronomical classification of the galaxies.
 
 
 
 
 
EPFL
BSc Physics
Sep 2013 – Jun 2016 Lausanne