| Kpconv: Flexible and deformable convolution for point clouds H Thomas, CR Qi, JE Deschaud, B Marcotegui, F Goulette, LJ Guibas Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 2602 | 2019 |
| Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods H Thomas, JE Deschaud, B Marcotegui, F Goulette, YL Gall 2018 International conference on 3D vision (3DV), 2018 | 160 | 2018 |
| Stpls3d: A large-scale synthetic and real aerial photogrammetry 3d point cloud dataset M Chen, Q Hu, Z Yu, H Thomas, A Feng, Y Hou, K McCullough, F Ren, ... arXiv preprint arXiv:2203.09065, 2022 | 56 | 2022 |
| Self-supervised learning of lidar segmentation for autonomous indoor navigation H Thomas, B Agro, M Gridseth, J Zhang, TD Barfoot 2021 IEEE International Conference on Robotics and Automation (ICRA), 14047 …, 2021 | 27 | 2021 |
| Exploring depth information for head detection with depth images S Chen, F Bremond, H Nguyen, H Thomas 2016 13th IEEE International Conference on Advanced Video and Signal Based …, 2016 | 17 | 2016 |
| Unsupervised learning of lidar features for use ina probabilistic trajectory estimator DJ Yoon, H Zhang, M Gridseth, H Thomas, TD Barfoot IEEE Robotics and Automation Letters 6 (2), 2130-2138, 2021 | 14 | 2021 |
| Learning spatiotemporal occupancy grid maps for lifelong navigation in dynamic scenes H Thomas, MG de Saint Aurin, J Zhang, TD Barfoot 2022 International Conference on Robotics and Automation (ICRA), 484-490, 2022 | 13 | 2022 |
| Rotation-invariant point convolution with multiple equivariant alignments H Thomas 2020 International Conference on 3D Vision (3DV), 504-513, 2020 | 12 | 2020 |
| Learning new representations for 3D point cloud semantic segmentation H Thomas Université Paris sciences et lettres, 2019 | 7 | 2019 |
| Safer: Safe collision avoidance using focused and efficient trajectory search with reinforcement learning M Srouji, H Thomas, YHH Tsai, A Farhadi, J Zhang 2023 IEEE 19th International Conference on Automation Science and …, 2023 | 4 | 2023 |
| The Foreseeable Future: Self-Supervised Learning to Predict Dynamic Scenes for Indoor Navigation H Thomas, J Zhang, TD Barfoot IEEE Transactions on Robotics, 2023 | 1 | 2023 |
| Embedding Pose Graph, Enabling 3D Foundation Model Capabilities with a Compact Representation H Thomas, J Zhang arXiv preprint arXiv:2403.13777, 2024 | | 2024 |
| KPConvX: Modernizing Kernel Point Convolution with Kernel Attention H Thomas, YHH Tsai, TD Barfoot, J Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Human Following in Mobile Platforms with Person Re-Identification M Srouji, YHH Tsai, H Thomas, J Zhang arXiv preprint arXiv:2309.12479, 2023 | | 2023 |
| Apprentissage de nouvelles représentations pour la sémantisation de nuages de points 3D H Thomas Paris Sciences et Lettres (ComUE), 2019 | | 2019 |
Jean-Emmanuel DeschaudAssociate Professor in Robotics and 3D Vision, Center for Robotics, Mines ParisTech, PSL University在 mines-paristech.fr 的电子邮件经过验证
