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I am a researcher at IGN, the French National Geographical Institute, in the machine learning team STRUDEL (LaSTIG, Univ. Gustave Eiffel). I am interested in optimization and machine learning for geospatial data such as 3D point clouds or satellite images time-series analysis.
I am the principal investigator of the ReADy3D ANR project on Dynamic 3D analysis for autonomous driving.
I am also co-program chair of the XXIVth ISPRS congress in Nice in 2022.
See my academic_CV for more details (updated in Apr 2022).

NEW! Our paper Deep View Aggregation with Damien Robert has been accepted at CVPR 2022 for an oral, and was selected as a best paper finalist 🏅!
NEW! 3 workshop papers at CVPR with my students Romain Loiseau and Ekaterina Kalinicheva : Transformers for Vision, Sight and Sound, and EarthVision.
NEW! Our CVPR Workshop EarthVision has been renewed for 2022. A great line-up of speakers, contests, and a must-attend event for researchers interested in both remote-sensing and computer vision.
NEW! Our paper with Vivien Sainte-Fare Garnot on leveraging class hierarchies has been accepted at BMVC 2021.
NEW! Our paper on the unsupervised and visual representation of large shape collections with Romain Loiseau, Tom Monnier, and Mathieu Aubry has been accepted at 3DV 2021.
NEW! Our paper on panoptic segmentation of satellite time series, with Vivien Sainte-Fare Garnot has been accepted at ICCV 2021. Check out PASTIS: the first SITS panoptic-ready dataset.

Selected Articles

Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation, Damien Robert, Bruno Vallet, Loic Landrieu CVPR 2022 (oral)
[arXiv] [github]

Deep Surface Reconstruction from Point Clouds with Visibility Information. Raphael Sulzer, Loic Landrieu, Alexandre Boulch, Renaud Marlet, Bruno Vallet, ICPR 2022
[arXiv] [github]


Representing Shape Collections with Alignment-Aware Linear Models, Romain Loiseau, Tom Monnier, Mathieu Aubry, Loic Landrieu 3DV 2021
[arXiv] [project] [github]


Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks, Vivien Sainte Fare Garnot Loic Landrieu, ICCV 2021
[arXiv] [github] [data]

Scalable Surface Reconstruction with Delaunay-Graph Neural Networks, Raphael Sulzer, Loic Landrieu, Renaud Marlet, and Bruno Vallet, Eurographics SGP 2021
[arXiv] [github]


Leveraging Class Hierarchies with Metric-Guided Prototype Learning, Vivien Sainte Fare Garnot, Loic Landrieu, BMVC 2021
[arXiv] [github]

Torch-Points3D: A Modular Multi-Task Framework for Reproducible Deep Learning on 3D Point Clouds, Thomas Chaton, Nicolas Chaulet, Sofiane Horache, Loic Landrieu, 3DV 2020 (oral)
[arXiv] [github]

Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention, Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano, Nesrine Chehata, CVPR 2020 (oral).
[arXiv] [github]


Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning, Loic Landrieu, Mohamed Boussaha, CVPR 2019.
[arXiv] [github]

Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation, Hugo Raguet and Loic Landrieu, ICML 2018 
[arXiv] [github]

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs, Loic landrieu and Martin Simonovsky, CVPR 2018.
[arXiv] [github]

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]

A Structured Regularization Framework for Spatially Smoothing Semantic Labelings of 3D Point Clouds. Loic Landrieu, Hugo Raguet , Bruno Vallet , Clément Mallet, Martin Weinmann, ISPRS Journal of Photogrammetry and Remote Sensing, 2017
[hal] [github]

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]

STUDENTS:

List of current and past PhD/Post Doc students:
Stéphane Guinard (Univ. Laval)
Mohamed Boussaha (Gambi-M)
Vivien Sainte-Fare Garnot (Univ. of Zurich)
Raphael Sulzer
Romain Loiseau
Damien Robert
Ekaterina Kalinicheva ‎(post doc)


List of current and past interns:
Stephane Guinard, Simon Bailly, Omar Lahbib, Joana Roussillon, Thomas Luo (Helix.Re), Anna Kondracka (Vermessung AVT), Lamiae El-Mendili, Ameur Zaibi, Julien Baconat, Cédric Baron, Félix Quinton, Yaping Lin, Dina El-Zein.

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

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

I review for ICML (top reviewer 2021), NeurIPS, ICCV, CVPR (outstanding reviewer 2021), ACCV, BMVC, IJCV, PAMI, ANRT, IJPRS, TIP, ISPRS (outstanding reviewer 2022) etc…

I am on the editorial board of IJPRS (Elsevier) and reviewing committee of Remote Sensing (MDPI).