Continuously indexed Potts models on unoriented graphs. - Loïc Landrieu; Guillaume Obozinski (UAI, 2014)

Preconditioning of a Generalized Forward-Backward Splitting and Application to Optimization on Graphs. - Hugo Raguet; Loïc Landrieu (SIAM J. Imaging Sci., 2015)

Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions. - Loïc Landrieu; Guillaume Obozinski (AISTATS, 2016)

Comparison of belief propagation and graph-cut approaches for contextual classification of 3D lidar point cloud data. - Loïc Landrieu; Clément Mallet; Martin Weinmann (IGARSS, 2017)

Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions on General Weighted Graphs. - Loïc Landrieu; Guillaume Obozinski (SIAM J. Imaging Sci., 2017)

Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs. - Loïc Landrieu; Martin Simonovsky (CVPR, 2018)

Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation. - Hugo Raguet; Loïc Landrieu (ICML, 2018)

Crop-Rotation Structured Classification using Multi-Source Sentinel Images and LPIS for Crop Type Mapping. - Simon Bailly; Sébastien Giordano; Loïc Landrieu; Nesrine Chehata (IGARSS, 2018)

Point Cloud Oversegmentation With Graph-Structured Deep Metric Learning. - Loïc Landrieu; Mohamed Boussaha (CVPR, 2019)

Time-Space Tradeoff in Deep Learning Models for Crop Classification on Satellite Multi-Spectral Image Time Series. - Vivien Sainte Fare Garnot; Loïc Landrieu; Sébastien Giordano; Nesrine Chehata (IGARSS, 2019)

Parallel Cut Pursuit For Minimization of the Graph Total Variation. - Hugo Raguet; Loïc Landrieu (CoRR, 2019)

Supervized Segmentation with Graph-Structured Deep Metric Learning. - Loïc Landrieu; Mohamed Boussaha (CoRR, 2019)

Torch-Points3D: A Modular Multi-Task Framework for Reproducible Deep Learning on 3D Point Clouds. - Thomas Chaton; Nicolas Chaulet; Sofiane Horache; Loïc Landrieu (3DV, 2020)

Satellite Image Time Series Classification With Pixel-Set Encoders and Temporal Self-Attention. - Vivien Sainte Fare Garnot; Loïc Landrieu; Sébastien Giordano; Nesrine Chehata (CVPR, 2020)

Lightweight Temporal Self-attention for Classifying Satellite Images Time Series. - Vivien Sainte Fare Garnot; Loïc Landrieu (AALTD@PKDD/ECML, 2020)

Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series. - Vivien Sainte Fare Garnot; Loïc Landrieu (CoRR, 2020)

Metric-Guided Prototype Learning. - Vivien Sainte Fare Garnot; Loïc Landrieu (CoRR, 2020)

Torch-Points3D: A Modular Multi-Task Frameworkfor Reproducible Deep Learning on 3D Point Clouds. - Thomas Chaton; Nicolas Chaulet; Sofiane Horache; Loïc Landrieu (CoRR, 2020)

Representing Shape Collections With Alignment-Aware Linear Models. - Romain Loiseau; Tom Monnier; Mathieu Aubry; Loïc Landrieu (3DV, 2021)

Leveraging Class Hierarchies with Metric-Guided Prototype Learning. - Vivien Sainte Fare Garnot; Loïc Landrieu (BMVC, 2021)

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks. - Vivien Sainte Fare Garnot; Loïc Landrieu (ICCV, 2021)

Scalable Surface Reconstruction with Delaunay-Graph Neural Networks. - Raphael Sulzer; Loïc Landrieu; Renaud Marlet; Bruno Vallet (Comput. Graph. Forum, 2021)

Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time Series. - Vivien Sainte Fare Garnot; Loïc Landrieu; Nesrine Chehata (CoRR, 2021)

Vegetation Stratum Occupancy Prediction from Airborne LiDAR 3D Point Clouds. - Ekaterina Kalinicheva; Loïc Landrieu; Clément Mallet; Nesrine Chehata (CoRR, 2021)

Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series. - Félix Quinton; Loïc Landrieu (Remote. Sens., 2021)

Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans. - Ekaterina Kalinicheva; Loïc Landrieu; Clément Mallet; Nesrine Chehata (CVPR Workshops, 2022)

Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation. - Damien Robert 002; Bruno Vallet; Loïc Landrieu (CVPR, 2022)

Online Segmentation of LiDAR Sequences: Dataset and Algorithm. - Romain Loiseau; Mathieu Aubry; Loïc Landrieu (ECCV (38), 2022)

Deep Surface Reconstruction from Point Clouds with Visibility Information. - Raphael Sulzer; Loïc Landrieu; Alexandre Boulch; Renaud Marlet; Bruno Vallet (ICPR, 2022)

A Model You Can Hear: Audio Identification with Playable Prototypes. - Romain Loiseau; Baptiste Bouvier; Yann Teytaut; Elliot Vincent; Mathieu Aubry; Loïc Landrieu (ISMIR, 2022)

Predicting Vegetation Stratum Occupancy from Airborne LiDAR Data with Deep Learning. - Ekaterina Kalinicheva; Loïc Landrieu; Clément Mallet; Nesrine Chehata (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Structured Learning of Geospatial Data. (Apprentissage Structuré de Données Géosaptiales). - Loïc Landrieu (2023)

Efficient 3D Semantic Segmentation with Superpoint Transformer. - Damien Robert 002; Hugo Raguet; Loïc Landrieu (ICCV, 2023)

FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery. - Anatol Garioud; Nicolas Gonthier; Loïc Landrieu; Apolline De Wit; Marion Valette; Marc Poupée; Sébastien Giordano; Boris Wattrelos (NeurIPS, 2023)

Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering. - Damien Robert 002; Hugo Raguet; Loïc Landrieu (3DV, 2024)

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; et al. (CVPR, 2024)

Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans. - Romain Loiseau; Elliot Vincent; Mathieu Aubry; Loïc Landrieu (CVPR, 2024)

StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation. - Sidi Wu; Yizi Chen; Samuel Mermet; Lorenz Hurni; Konrad Schindler; Nicolas Gonthier; Loïc Landrieu (CVPR, 2024)

OmniSat: Self-supervised Modality Fusion for Earth Observation. - Guillaume Astruc; Nicolas Gonthier; Clément Mallet; Loïc Landrieu (ECCV (28), 2024)

Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era. - Yohann Perron; Vladyslav Sydorov; Adam P. Wijker; Damian Evans; Christophe Pottier; Loïc Landrieu (NeurIPS, 2024)

Scalable 3D Panoptic Segmentation With Superpoint Graph Clustering. - Damien Robert 002; Hugo Raguet; Loïc Landrieu (CoRR, 2024)

Open-Canopy: A Country-Scale Benchmark for Canopy Height Estimation at Very High Resolution. - Fajwel Fogel; Yohann Perron; Nikola Besic; Laurent Saint-André; Agnès Pellissier-Tanon; Martin Schwartz; Thomas Boudras; Ibrahim Fayad; Alexandre d'Aspremont; Loïc Landrieu; Philippe Ciais (CoRR, 2024)

AnySat: An Earth Observation Model for Any Resolutions, Scales, and Modalities. - Guillaume Astruc; Nicolas Gonthier; Clément Mallet; Loïc Landrieu (CoRR, 2024)

Dataset for the paper: "StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation", CVPR 2024. - Sidi Wu; Yizi Chen; Samuel Mermet; Lorenz Hurni; Konrad Schindler; Nicolas Gonthier; Loïc Landrieu (Zenodo, 2024)

AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities. - Guillaume Astruc; Nicolas Gonthier; Clément Mallet; Loïc Landrieu (CVPR, 2025)

Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation. - Nicolas Dufour; Vicky Kalogeiton; David Picard; Loïc Landrieu (CVPR, 2025)

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; Loïc Landrieu; Philippe Ciais (CVPR, 2025)

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis. - Abhishek Kuriyal; Elliot Vincent; Mathieu Aubry; Loïc Landrieu (CVPR Workshops, 2025)

A Survey and Benchmark of Automatic Surface Reconstruction From Point Clouds. - Raphael Sulzer; Renaud Marlet; Bruno Vallet; Loïc Landrieu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Segmenting France Across Four Centuries. - Marta López-Rauhut; Hongyu Zhou; Mathieu Aubry; Loïc Landrieu (CoRR, 2025)