| Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs L Landrieu, M Simonovsky CVPR 2018, 2017 | 1490 | 2017 |
| Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning L Landrieu, M Boussaha CVPR 2019, 2019 | 217 | 2019 |
| Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention V Sainte Fare Garnot, L Landrieu, S Giordano, N Chehata CVPR 2020, 2019 | 186* | 2019 |
| Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks V Sainte Fare Garnot, L Landrieu ICCV 2021, 2021 | 154* | 2021 |
| A structured regularization framework for spatially smoothing semantic labelings of 3D point clouds L Landrieu, H Raguet, B Vallet, C Mallet, M Weinmann ISPRS journal of Photogrammetry and Remote Sensing 132, Pages 102-118, 2017 | 119 | 2017 |
| Weakly supervised segmentation-aided classification of urban scenes from 3D LiDAR point clouds S Guinard, L Landrieu ISPRS - International Archives of the Photogrammetry, Remote Sensing and …, 2017 | 118 | 2017 |
| Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series V Sainte Fare Garnot, L Landrieu International Workshop on Advanced Analysis and Learning on Temporal Data, 2020 | 94* | 2020 |
| Cut pursuit: Fast algorithms to learn piecewise constant functions on general weighted graphs L Landrieu, G Obozinski SIAM Journal on Imaging Sciences 10 (4), 1724-1766, 2017 | 87 | 2017 |
| Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time Series V Sainte Fare Garnot, L Landrieu, N Chehata International Journal of Photogrammetry and Remote Sensing (IJPRS), 2021 | 70* | 2021 |
| Time-Space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series VSF Garnot, L Landrieu, S Giordano, N Chehata IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019 | 68 | 2019 |
| Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation D Robert, B Vallet, L Landrieu CVPR 2022, 2022 | 66 | 2022 |
| Preconditioning of a generalized forward-backward splitting and application to optimization on graphs H Raguet, L Landrieu SIAM Journal on Imaging Sciences 8 (4), 2706-2739, 2015 | 51 | 2015 |
| Torch-Points3D: A Modular Multi-Task Framework for Reproducible Deep Learning on 3D Point Clouds T Chaton, N Chaulet, S Horache, L Landrieu 3DV 2020, 2020 | 48 | 2020 |
| Efficient 3D Semantic Segmentation with Superpoint Transformer D Robert, H Raguet, L Landrieu ICCV 2023, 2023 | 33 | 2023 |
| Leveraging Class Hierarchies with Metric-Guided Prototype Learning L Landrieu, VSF Garnot BMVC 2021, 2021 | 33* | 2021 |
| Improved crop classification with rotation knowledge using sentinel-1 and-2 time series S Giordano, S Bailly, L Landrieu, N Chehata Photogrammetric Engineering & Remote Sensing, 2020 | 23 | 2020 |
| Comparison of belief propagation and graph-cut approaches for contextual classification of 3D lidar point cloud data L Landrieu, C Mallet, M Weinmann 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017 | 20 | 2017 |
| Cut Pursuit: fast algorithms to learn piecewise constant functions L Landrieu, G Obozinski Artificial Intelligence and Statistics, 1384-1393, 2016 | 20 | 2016 |
| Online Segmentation of LiDAR Sequences: Dataset and Algorithm R Loiseau, M Aubry, L Landrieu ECCV 2022, 2022 | 17 | 2022 |
| A survey and benchmark of automatic surface reconstruction from point clouds R Sulzer, R Marlet, B Vallet, L Landrieu arXiv preprint arXiv:2301.13656, 2023 | 13 | 2023 |
