| 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 | 733 | 2018 |
| 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 | 550* | 2018 |
| 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 | 311 | 2018 |
| ConvPoint: Continuous convolutions for point cloud processing A Boulch Computers & Graphics 88, 24-34, 2020 | 247* | 2020 |
| 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 | 203* | 2019 |
| Fast and robust normal estimation for point clouds with sharp features A Boulch, R Marlet Computer graphics forum 31 (5), 1765-1774, 2012 | 188 | 2012 |
| Flot: Scene flow on point clouds guided by optimal transport G Puy, A Boulch, R Marlet European conference on computer vision, 527-544, 2020 | 135 | 2020 |
| 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 | 122 | 2016 |
| Deep learning for robust normal estimation in unstructured point clouds A Boulch, R Marlet Computer Graphics Forum 35 (5), 281-290, 2016 | 122 | 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 | 107 | 2015 |
| 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 | 98 | 2018 |
| 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 | 91 | 2017 |
| 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 | 64 | 2014 |
| Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance suite, dataset analysis and multi-task network study J Castillo-Navarro, B Le Saux, A Boulch, N Audebert, S Lefèvre Machine Learning, 1-36, 2021 | 62 | 2021 |
| FKAConv: Feature-Kernel Alignment for Point Cloud Convolution A Boulch, G Puy, R Marlet Proceedings of the Asian Conference on Computer Vision, 2020 | 58 | 2020 |
| Poco: Point convolution for surface reconstruction A Boulch, R Marlet Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 56 | 2022 |
| Image-to-lidar self-supervised distillation for autonomous driving data C Sautier, G Puy, S Gidaris, A Boulch, A Bursuc, R Marlet Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 55 | 2022 |
| Reducing parameter number in residual networks by sharing weights A Boulch Pattern Recognition Letters 103, 53-59, 2018 | 42* | 2018 |
| 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 | 41 | 2019 |
| Generative zero-shot learning for semantic segmentation of 3d point clouds B Michele, A Boulch, G Puy, M Bucher, R Marlet 2021 International Conference on 3D Vision (3DV), 992-1002, 2021 | 40 | 2021 |
Bertrand Le SauxESA / ESRIN Φ-labVerified email at ieee.org
