default search action
Loïc Landrieu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c26]Damien Robert, Hugo Raguet, Loïc Landrieu:
Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering. 3DV 2024: 179-189 - [c25]Sidi Wu, Yizi Chen, Samuel Mermet, Lorenz Hurni, Konrad Schindler, Nicolas Gonthier, Loïc Landrieu:
StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation. CVPR 2024: 7922-7931 - [c24]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, Loïc Landrieu:
OpenStreetView-5M: The Many Roads to Global Visual Geolocation. CVPR 2024: 21967-21977 - [c23]Romain Loiseau, Elliot Vincent, Mathieu Aubry, Loïc Landrieu:
Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans. CVPR 2024: 27874-27884 - [c22]Guillaume Astruc
, Nicolas Gonthier, Clément Mallet, Loïc Landrieu:
OmniSat: Self-supervised Modality Fusion for Earth Observation. ECCV (28) 2024: 409-427 - [i30]Damien Robert, Hugo Raguet, Loïc Landrieu:
Scalable 3D Panoptic Segmentation With Superpoint Graph Clustering. CoRR abs/2401.06704 (2024) - [i29]Sidi Wu, Yizi Chen, Samuel Mermet, Lorenz Hurni, Konrad Schindler, Nicolas Gonthier, Loïc Landrieu:
StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation. CoRR abs/2403.20142 (2024) - [i28]Guillaume Astruc, Nicolas Gonthier, Clément Mallet, Loïc Landrieu:
OmniSat: Self-Supervised Modality Fusion for Earth Observation. CoRR abs/2404.08351 (2024) - [i27]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, Loïc Landrieu:
OpenStreetView-5M: The Many Roads to Global Visual Geolocation. CoRR abs/2404.18873 (2024) - [i26]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:
Open-Canopy: A Country-Scale Benchmark for Canopy Height Estimation at Very High Resolution. CoRR abs/2407.09392 (2024) - 2023
- [b1]Loïc Landrieu:
Structured Learning of Geospatial Data. (Apprentissage Structuré de Données Géosaptiales). École des ponts ParisTech, Champs-sur-Marne, France, 2023 - [c21]Damien Robert
Efficient 3D Semantic Segmentation with Superpoint Transformer. ICCV 2023: 17149-17158 - [c20]Anatol Garioud, Nicolas Gonthier, Loïc Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sébastien Giordano, Boris Wattrelos:
FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery. NeurIPS 2023 - [i25]Raphael Sulzer, Loïc Landrieu, Renaud Marlet, Bruno Vallet:
A Survey and Benchmark of Automatic Surface Reconstruction from Point Clouds. CoRR abs/2301.13656 (2023) - [i24]Romain Loiseau, Elliot Vincent, Mathieu Aubry, Loïc Landrieu:
Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans. CoRR abs/2304.09704 (2023) - [i23]Damien Robert, Hugo Raguet, Loïc Landrieu:
Efficient 3D Semantic Segmentation with Superpoint Transformer. CoRR abs/2306.08045 (2023) - [i22]Anatol Garioud, Nicolas Gonthier, Loïc Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sébastien Giordano, Boris Wattrelos:
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery. CoRR abs/2310.13336 (2023) - 2022
- [j5]Ekaterina Kalinicheva, Loïc Landrieu, Clément Mallet, Nesrine Chehata:
Predicting Vegetation Stratum Occupancy from Airborne LiDAR Data with Deep Learning. Int. J. Appl. Earth Obs. Geoinformation 112: 102863 (2022) - [c19]Ekaterina Kalinicheva, Loïc Landrieu, Clément Mallet, Nesrine Chehata:
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans. CVPR Workshops 2022: 1341-1350 - [c18]Damien Robert
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation. CVPR 2022: 5565-5574 - [c17]Romain Loiseau
Online Segmentation of LiDAR Sequences: Dataset and Algorithm. ECCV (38) 2022: 301-317 - [c16]Raphael Sulzer, Loïc Landrieu, Alexandre Boulch, Renaud Marlet, Bruno Vallet:
Deep Surface Reconstruction from Point Clouds with Visibility Information. ICPR 2022: 2415-2422 - [c15]Romain Loiseau, Baptiste Bouvier, Yann Teytaut, Elliot Vincent, Mathieu Aubry, Loïc Landrieu:
A Model You Can Hear: Audio Identification with Playable Prototypes. ISMIR 2022: 694-700 - [i21]Ekaterina Kalinicheva, Loïc Landrieu, Clément Mallet, Nesrine Chehata:
Predicting Vegetation Stratum Occupancy from Airborne LiDAR Data with Deep Learning. CoRR abs/2201.08051 (2022) - [i20]Raphael Sulzer, Loïc Landrieu, Alexandre Boulch, Renaud Marlet, Bruno Vallet:
Deep Surface Reconstruction from Point Clouds with Visibility Information. CoRR abs/2202.01810 (2022) - [i19]Damien Robert, Bruno Vallet, Loïc Landrieu:
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation. CoRR abs/2204.07548 (2022) - [i18]Ekaterina Kalinicheva, Loïc Landrieu, Clément Mallet, Nesrine Chehata:
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans. CoRR abs/2204.11620 (2022) - [i17]Romain Loiseau, Mathieu Aubry, Loïc Landrieu:
Online Segmentation of LiDAR Sequences: Dataset and Algorithm. CoRR abs/2206.08194 (2022) - [i16]Romain Loiseau, Baptiste Bouvier, Yann Teytaut, Elliot Vincent, Mathieu Aubry, Loïc Landrieu:
A Model You Can Hear: Audio Identification with Playable Prototypes. CoRR abs/2208.03311 (2022) - 2021
- [j4]Raphael Sulzer
Scalable Surface Reconstruction with Delaunay-Graph Neural Networks. Comput. Graph. Forum 40(5): 157-167 (2021) - [j3]Félix Quinton
Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series. Remote. Sens. 13(22): 4599 (2021) - [c14]Romain Loiseau, Tom Monnier, Mathieu Aubry, Loïc Landrieu:
Representing Shape Collections With Alignment-Aware Linear Models. 3DV 2021: 1044-1053 - [c13]Vivien Sainte Fare Garnot, Loïc Landrieu:
Leveraging Class Hierarchies with Metric-Guided Prototype Learning. BMVC 2021: 123 - [c12]Vivien Sainte Fare Garnot, Loïc Landrieu:
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks. ICCV 2021: 4852-4861 - [i15]Raphael Sulzer, Loïc Landrieu, Renaud Marlet, Bruno Vallet:
Scalable Surface Reconstruction with Delaunay-Graph Neural Networks. CoRR abs/2107.06130 (2021) - [i14]Vivien Sainte Fare Garnot, Loïc Landrieu:
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks. CoRR abs/2107.07933 (2021) - [i13]Romain Loiseau
Representing Shape Collections with Alignment-Aware Linear Models. CoRR abs/2109.01605 (2021) - [i12]Félix Quinton, Loïc Landrieu:
Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series. CoRR abs/2110.08187 (2021) - [i11]Vivien Sainte Fare Garnot, Loïc Landrieu, Nesrine Chehata:
Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time Series. CoRR abs/2112.07558 (2021) - [i10]Ekaterina Kalinicheva, Loïc Landrieu, Clément Mallet, Nesrine Chehata:
Vegetation Stratum Occupancy Prediction from Airborne LiDAR 3D Point Clouds. CoRR abs/2112.13583 (2021) - 2020
- [c11]Thomas Chaton, Nicolas Chaulet, Sofiane Horache, Loïc Landrieu:
Torch-Points3D: A Modular Multi-Task Framework for Reproducible Deep Learning on 3D Point Clouds. 3DV 2020: 190-199 - [c10]Vivien Sainte Fare Garnot, Loïc Landrieu, Sébastien Giordano, Nesrine Chehata
Satellite Image Time Series Classification With Pixel-Set Encoders and Temporal Self-Attention. CVPR 2020: 12322-12331 - [c9]Vivien Sainte Fare Garnot, Loïc Landrieu:
Lightweight Temporal Self-attention for Classifying Satellite Images Time Series. AALTD@PKDD/ECML 2020: 171-181 - [i9]Vivien Sainte Fare Garnot, Loïc Landrieu:
Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series. CoRR abs/2007.00586 (2020) - [i8]Vivien Sainte Fare Garnot, Loïc Landrieu:
Metric-Guided Prototype Learning. CoRR abs/2007.03047 (2020) - [i7]Thomas Chaton, Nicolas Chaulet, Sofiane Horache, Loïc Landrieu:
Torch-Points3D: A Modular Multi-Task Frameworkfor Reproducible Deep Learning on 3D Point Clouds. CoRR abs/2010.04642 (2020)
2010 – 2019
- 2019
- [c8]Loïc Landrieu, Mohamed Boussaha:
Point Cloud Oversegmentation With Graph-Structured Deep Metric Learning. CVPR 2019: 7440-7449 - [c7]Vivien Sainte Fare Garnot, Loïc Landrieu, Sébastien Giordano, Nesrine Chehata:
Time-Space Tradeoff in Deep Learning Models for Crop Classification on Satellite Multi-Spectral Image Time Series. IGARSS 2019: 6247-6250 - [i6]Vivien Sainte Fare Garnot
Time-Space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series. CoRR abs/1901.10503 (2019) - [i5]Loïc Landrieu, Mohamed Boussaha:
Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning. CoRR abs/1904.02113 (2019) - [i4]Hugo Raguet, Loïc Landrieu:
Parallel Cut Pursuit For Minimization of the Graph Total Variation. CoRR abs/1905.02316 (2019) - [i3]Loïc Landrieu, Mohamed Boussaha:
Supervized Segmentation with Graph-Structured Deep Metric Learning. CoRR abs/1905.04014 (2019) - [i2]Vivien Sainte Fare Garnot
Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention. CoRR abs/1911.07757 (2019) - 2018
- [c6]Loïc Landrieu, Martin Simonovsky:
Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs. CVPR 2018: 4558-4567 - [c5]Hugo Raguet, Loïc Landrieu:
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation. ICML 2018: 4244-4253 - [c4]Simon Bailly, Sébastien Giordano, Loïc Landrieu, Nesrine Chehata
Crop-Rotation Structured Classification using Multi-Source Sentinel Images and LPIS for Crop Type Mapping. IGARSS 2018: 1950-1953 - 2017
- [j2]Loïc Landrieu, Guillaume Obozinski
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions on General Weighted Graphs. SIAM J. Imaging Sci. 10(4): 1724-1766 (2017) - [c3]Loïc Landrieu, Clément Mallet, Martin Weinmann
Comparison of belief propagation and graph-cut approaches for contextual classification of 3D lidar point cloud data. IGARSS 2017: 2768-2771 - [i1]Loïc Landrieu, Martin Simonovsky:
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs. CoRR abs/1711.09869 (2017) - 2016
- [c2]Loïc Landrieu, Guillaume Obozinski:
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions. AISTATS 2016: 1384-1393 - 2015
- [j1]Hugo Raguet, Loïc Landrieu:
Preconditioning of a Generalized Forward-Backward Splitting and Application to Optimization on Graphs. SIAM J. Imaging Sci. 8(4): 2706-2739 (2015) - 2014
- [c1]Loïc Landrieu, Guillaume Obozinski:
Continuously indexed Potts models on unoriented graphs. UAI 2014: 459-468
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-02 22:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: