| SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks A Boulch, J Guerry, B Le Saux, N Audebert Computers & Graphics 71, 189-198, 2018 | 206* | 2018 |
| Fast and robust normal estimation for point clouds with sharp features A Boulch, R Marlet Computer graphics forum 31 (5), 1765-1774, 2012 | 125 | 2012 |
| Fully convolutional siamese networks for change detection RC Daudt, B Le Saux, A Boulch 2018 25th IEEE International Conference on Image Processing (ICIP), 4063-4067, 2018 | 89 | 2018 |
| Processing of extremely high-resolution Lidar and RGB data: outcome of the 2015 IEEE GRSS data fusion contest–part a: 2-D contest M Campos-Taberner, A Romero-Soriano, C Gatta, G Camps-Valls, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2016 | 82 | 2016 |
| Benchmarking classification of earth-observation data: From learning explicit features to convolutional networks A Lagrange, B Le Saux, A Beaupere, A Boulch, A Chan-Hon-Tong, ... 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2015 | 77 | 2015 |
| Urban change detection for multispectral earth observation using convolutional neural networks RC Daudt, B Le Saux, A Boulch, Y Gousseau IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 67 | 2018 |
| Deep learning for robust normal estimation in unstructured point clouds A Boulch, R Marlet Computer Graphics Forum 35 (5), 281-290, 2016 | 62 | 2016 |
| Large-scale semantic classification: outcome of the first year of inria aerial image labeling benchmark B Huang, K Lu, N Audeberr, A Khalel, Y Tarabalka, J Malof, A Boulch, ... IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 56 | 2018 |
| Piecewise‐planar 3D reconstruction with edge and corner regularization A Boulch, M de La Gorce, R Marlet Computer Graphics Forum 33 (5), 55-64, 2014 | 44 | 2014 |
| ConvPoint: Continuous convolutions for point cloud processing A Boulch Computers & Graphics 88, 24-34, 2020 | 33* | 2020 |
| Snapnet-r: Consistent 3d multi-view semantic labeling for robotics J Guerry, A Boulch, B Le Saux, J Moras, A Plyer, D Filliat Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 33 | 2017 |
| Multitask learning for large-scale semantic change detection RC Daudt, B Le Saux, A Boulch, Y Gousseau Computer Vision and Image Understanding 187, 102783, 2019 | 32* | 2019 |
| Reducing parameter number in residual networks by sharing weights A Boulch Pattern Recognition Letters 103, 53-59, 2018 | 27* | 2018 |
| Irreducible triangulations of surfaces with boundary A Boulch, ÉC de Verdière, A Nakamoto Graphs and Combinatorics 29 (6), 1675-1688, 2013 | 25 | 2013 |
| Semantizing complex 3D scenes using constrained attribute grammars A Boulch, S Houllier, R Marlet, O Tournaire Computer Graphics Forum 32 (5), 33-42, 2013 | 23 | 2013 |
| Deep learning for urban remote sensing N Audebert, A Boulch, H Randrianarivo, B Le Saux, M Ferecatu, S Lefevre, ... 2017 Joint Urban Remote Sensing Event (JURSE), 1-4, 2017 | 20 | 2017 |
| SHREC'17: Deformable shape retrieval with missing parts E Rodolà, L Cosmo, O Litany, MM Bronstein, AM Bronstein, N Audebert, ... 10th Eurographics Workshop on 3D Object Retrieval, 3DOR 2017, 85-94, 2017 | 20 | 2017 |
| Retrieval of forest vertical structure from PolInSAR Data by machine learning using LIDAR-Derived features G Brigot, M Simard, E Colin-Koeniguer, A Boulch Remote Sensing 11 (4), 381, 2019 | 10 | 2019 |
| Distance transform regression for spatially-aware deep semantic segmentation N Audebert, A Boulch, B Le Saux, S Lefèvre Computer Vision and Image Understanding 189, 102809, 2019 | 9 | 2019 |
| Point-cloud shape retrieval of non-rigid toys: Shrec'17 track FA Limberger, RC Wilson, M Aono, N Audebert, A Boulch, B Bustos, ... Proceedings of the Workshop on 3D Object Retrieval, 75-84, 2017 | 9 | 2017 |
