Home


github
scholar
linkedin
orcid
CV
email

I am a machine learning researcher at Imagine (A3SI/LIGM, ENPC, IP-Paris), Senior Hi!Paris Fellow, and associate researcher at IGN in the LASTIG lab. I am interested in:
Multimodality Environment Frugal AI Geolocation3D Deep Learning

Area Chair: NeurIPS’26, CVPR’26, 3DV’26, CVPR’25, ECCV’24, IGARSS’24
Program Chair: CVPR Workshop EarthVision (2021-2026), EurIPS Workshop Representation Learning for Earth Observation (2025), XXIVth ISPRS congress (2022)
Outstanding Reviewer: NeurIPS’25, ICCV’23, ECCV’22, ICML’21, CVPR’21, IJPRS’21&22

NEWS

🆕 UniGeoCLIP accepted at CVPR’26 Workshop EarthVision
🆕 VRSketch2Shape accepted at CVPR’26
🆕 PoM accepted at CVPR‘26 Findings
🆕 EZ-SP accepted to ICRA2026
🆕 CVPR’26 Workshop EarthVision is renewed for its 9th edition
🆕 Relay Tokens has been accepted to TMLR

More updates

🆕 I will present my work at Meta FAIR, Google Deepmind, EPFL, ETH Zurich, EGU, INRIA LIRMM, Copenhagen Pioneer Centre for AI, IADF OrbitTracks, and Paris Saclay Summit
🆕 We are organizing the 1st workshop on Representation Learning for Earth Observation at Eurips 2025
🆕 Our paper on historical maps has been accepted to ICDAR2025 as an oral 🎤
🆕 4 new grants: ANR DEEPFOREST with LSCE and EFEO (666k€), senior Hi! Paris senior fellowship (360k€), DIM PAMIR with EFEO (75k€), CNES post-doc with LSCE (140k€)
🆕 👏 Congrats to my former student Damien Robert for recieving an accessit to the AFRIF PhD Award
🆕 3 papers accepted at CVPR2025: AnySat (highlight ✨), Generative Geoloc, and Open-Canopy (highlight ✨)

SELECTED ARTICLES

FORMSpoT: A Decade of Tree-Level, Country-Scale Forest Monitoring, Martin Schwartz, Fajwel Fogel, Nikola Besic, Damien Robert, Louis Geist, Jean-Pierre Renaud, Jean-Matthieu Monnet, Clemens Mosig, Cédric Vega, Alexandre d’Aspremont, Loic Landrieu, Philippe Ciais,
2026
[arxiv] [data]
EnvironmentMultimodality

🍏PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer, David Picard, Nicolas Dufour, Lucas Degeorge, Arijit Ghosh, Davide Allegro, Tom Ravaud, Yohann Perron, Corentin Sautier, Zeynep Sonat Baltaci, Fei Meng, Syrine Kalleli, Marta López-Rauhut, Thibaut Loiseau, Ségolène Albouy, Raphael Baena, Elliot Vincent, Loic Landrieu
CVPR’2026 Findings
[arxiv] [github]
Frugality

Order Matters: 3D Shape Generation from Sequential VR Sketches, Yizi Chen, Sidi Wu, Tianyi Xiao, Nina Wiedemann, Loic Landrieu
CVPR‘26
[arxiv] [gihub] [project]
3D Deep Learning

EZ-SP: Fast and Lightweight Superpoint-Based 3D Segmentation, Louis Geist, Loic Landrieu, Damien Robert.
ICRA‘26
[arxiv] [project]
3D Deep Learning Frugality

Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokens, Yohann Perron, Vladyslav Sydorov, Christophe Pottier, Loic Landrieu,
TMLR 2025
[arxiv] [project]
Frugality

Segmenting France Across Four Centuries, Marta LĂłpez-Rauhut, Hongyu Zhou, Mathieu Aubry, Loic Landrieu,
ICDAR'25 (oral 🎤, top 8%)
[arxiv] [data] [github]
Historical Frugality

AnySat: An Earth Observation Model for Any Resolutions, Scales, and Modalities, Guillaume Astruc, Nicolas Gonthier, Clement Mallet, Loic Landrieu,
CVPR'25 (highlight ✨ top 3%)
[arXiv] [project] [models]
Environment Multimodality

Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation, Nicolas Dufour, David Picard, Vicky Kalogeiton, Loic Landrieu,
CVPR'25
[arXiv] [demo] [project] [models]
Geolocation

Open-Canopy: Towards Very High Resolution Forest Monitoring, Fajwel Fogel, Yohann Perron, Nikola Besic, Laurent Saint-André, Agnès Pellissier-Tanon, Martin Schwartz, Thomas Boudras, Ibrahim Fayad, Alexandre d’Aspremont, Loic Landrieu, Phillipe Ciais,
CVPR'25 (highlight ✨ top 3%)
[arXiv] [github and data]
Environment Multimodality

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis. Abhishek Kuriyal, Elliot Vincent, Mathieu Aubry, and Loic Landrieu,
CVPR'25 Workshop EarthVision
[arXiv] [project]
Environment

A Survey and Benchmark of Automatic Surface Reconstruction from Point Clouds Raphael Sulzer, Renaud Marlet, Bruno Vallet, Loic Landrieu,
TPAMI 2024
[arXiv] [github and data]
3D Deep Learning

Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era, Yohann Perron*,Vladyslav Sydorov*, Adam P. Wijker, Damian Evans, Christophe Pottier, Loic Landrieu,
NeurIPS Benchmark & Dataset '24 (splotlight ✨ top 3%)
[paper] [github and data]
Historical

OmniSat: Self-Supervised Modality Fusion for Earth Observation, Guillaume Astruc, Nicolas Gonthier, Clément Mallet, Loic Landrieu,
ECCV'24
[arXiv] [github and data]
Environment Multimodality

OpenStreetView-5M: The Many Roads to Global Visual Geolocation, Guillaume Astruc*, Nicolas Dufour*, Ioannis Siglidis*, Constantin Aronssohn, Nacim Bouia, Stephanie Fu, Romain Loiseau, Van Nguyen Nguyen, Charles Raude, Elliot Vincent, Lintao XU, Hongyu Zhou, Loic Landrieu,
CVPR'24.
[demo] [paper] [data] [project]
Geolocation

Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans, Romain Loiseau, Elliot Vincent, Mathieu Aubry, Loic Landrieu,
CVPR'24.
[github] [arXiv] [project] [data]
3D Deep Learning FrugalityEnvironment

StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation, Sidi Wu*, Yizi Chen*, Samuel Mermet, Lorenz Hurni, Nicolas Gonthier, Konrad Schindler, Loic Landrieu,
CVPR'24.
[github] [arXiv] [data]
Machine Learning

Scalable 3D Panoptic Segmentation as Superpoint Graph Clustering, Damien Robert, Hugo Raguet, Loic Landrieu,
3DV'24 (oral 🎤 top 5%).
[github] [arXiv]
3D Deep Learning Frugality

FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery, Anatol Garioud, Nicolas Gonthier, Loic Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sébastien Giordano, Boris Wattrelos
NeurIPS Dataset and Benchmark'23.
[challenge] [github] [arXiv]
Environment Multimodality

Efficient 3D Semantic Segmentation with Superpoint Transformer, Damien Robert, Hugo Raguet, Loic Landrieu,
ICCV '23.
[project] [arXiv] [github]
3D Deep Learning Frugality

Online Segmentation of LiDAR Sequences: Dataset and Algorithm, Romain Loiseau, Mathieu Aubry, Loic Landrieu,
ECCV'22.
[arXiv] [github] [data] [project]
3D Deep Learning Frugality

Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation, Damien Robert, Bruno Vallet, Loic Landrieu,
CVPR'22 (oral 🎤, best paper finalist 🏅top 0.4%).
[arXiv] [github]
3D Deep Learning Multimodality

Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans, Ekaterina Kalinicheva, Loic Landrieu, Clement Mallet, Nesrine Chehata,
CVPR'22 Workshop EarthVision.
[arXiv] [github]
Environment3D Deep Learning

Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time Series, Vivien Sainte Fare Garnot, Loic Landrieu, 
ISPRS Journal of Photogrammetry and Remote Sensing 2022.
 [arXiv] [data] [github]
Environment Multimodality


Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks, Vivien Sainte Fare Garnot, Loic Landrieu,
ICCV'21.
[arXiv] [github] [data]
Environment Multimodality

Leveraging Class Hierarchies with Metric-Guided Prototype Learning, Vivien Sainte Fare Garnot, Loic Landrieu,
BMVC'21.
[arXiv] [github]
Machine LearningEnvironment

Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention, Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano, Nesrine Chehata,
CVPR'20 (oral 🎤 top 5%).
[arXiv] [github]
Environment

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning, Loic Landrieu, Mohamed Boussaha,
CVPR'19.
[arXiv] [github]
3D Deep Learning Frugality

Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation, Hugo Raguet, Loic Landrieu,
ICML'18. 
[arXiv] [github]
Machine Learning

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs, Loic Landrieu* and Martin Simonovsky*,
CVPR'18.
[arXiv] [github]
3D Deep Learning Frugality

Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions on General Weighted Graphs. Loic Landrieu, Guillaume Obozinski, 
SIAM Journal on Imaging Science 2017.
[hal][github]
Machine Learning

Preconditioning of a Generalized Forward-Backward Splitting and Application to Optimization on Graphs. Hugo Raguet, Loic Landrieu,
SIAM Journal on Imaging Science, 2015.
[arxiv] [github]
Machine Learning

COMMUNITY

- Area Chair for CVPR'26, 3D'V26, CVPR'25, ECCV'24 and IGARSS'24.
- Work Package Leader for the SHARP PEPR on Frugal AI
- Co-chair of the ISPRS working group Temporal Geospatial Data Understanding
- Co-organizer of the EarthVision CVPR Workshop (2021,2022,2023,2024,2025)
- Co-organizer of the Representation Learning for Earth Observation (REO) workshop at EurIPS (2025)
- Co-Program chair of the XXIVth ISPRS congress
- Editorial Advisory Board of ISPRS Journal (Elsevier, IF:11.8) & Reviewing Committee of Remote Sensing (MDPI, IF:5.3)
- ELLIS member.

Reviewer for: ICML, NeurIPS, ICCV, ECCV, CVPR, ACCV, BMVC, IJCV, PAMI, ANRT, IJPRS, TIP, ISPRS etc...
Oustanding reviewer for: NeurIPS2025, ICCV2023, ECCV22, ICML21, CVPR21, ISPRS-Congress22, ISPRS Journal 2021 & 2022.

STUDENTS:

List of current and past PhD/Post Doc students:

List of current and past interns:
Stephane Guinard, Simon Bailly, Omar Lahbib, Joana Roussillon, Thomas Luo , Anna Kondracka, Lamiae El-Mendili, Ameur Zaibi, Julien Baconat, CĂ©dric Baron, FĂ©lix Quinton, Yaping Lin, Dina El-Zein, Hongyu Zhou, Guillaume Astruc, Jakub Vynikal, Abishek Kuriya

MISC

I teach machine learning at master level at MVA, ENSG and ENPC.

I am a technical advisor for SAMP, a startup using machine learning to produce digital twins of industrial facilities.

I offer machine learning / computer vision consulting. Notable clients include QuantCube, Helix.re, Samp.ai, Gambi-M, Eurobios Mews Labs.