Hugues Thomas

According to our database, Hugues Thomas authored at least 16 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Embedding Pose Graph, Enabling 3D Foundation Model Capabilities with a Compact Representation.

Hugues Thomas, Jian Zhang

CoRR, 2024

2023

The Foreseeable Future: Self-Supervised Learning to Predict Dynamic Scenes for Indoor Navigation.

Hugues Thomas, Jian Zhang, Timothy D. Barfoot

IEEE Trans. Robotics, December, 2023

Human Following in Mobile Platforms with Person Re-Identification.

Mario Srouji, Yao-Hung Hubert Tsai, Hugues Thomas, Jian Zhang

CoRR, 2023

SAFER: Safe Collision Avoidance Using Focused and Efficient Trajectory Search with Reinforcement Learning.

Mario Srouji, Hugues Thomas, Yao-Hung Hubert Tsai, Ali Farhadi, Jian Zhang

Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023

2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

Meida Chen, Qingyong Hu, Hugues Thomas, Andrew Feng, Yu Hou, Kyle McCullough, Lucio Soibelman

CoRR, 2022

Learning Spatiotemporal Occupancy Grid Maps for Lifelong Navigation in Dynamic Scenes.

Hugues Thomas, Matthieu Gallet de Saint Aurin, Jian Zhang, Timothy D. Barfoot

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset.

Meida Chen, Qingyong Hu, Zifan Yu, Hugues Thomas, Andrew Feng, Yu Hou, Kyle McCullough, Fengbo Ren, Lucio Soibelman

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Unsupervised Learning of Lidar Features for Use ina Probabilistic Trajectory Estimator.

David J. Yoon, Haowei Zhang, Mona Gridseth, Hugues Thomas, Timothy D. Barfoot

IEEE Robotics Autom. Lett., 2021

Unsupervised Learning of Lidar Features for Use in a Probabilistic Trajectory Estimator.

David J. Yoon, Haowei Zhang, Mona Gridseth, Hugues Thomas, Timothy D. Barfoot

CoRR, 2021

Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor Navigation.

Hugues Thomas, Ben Agro, Mona Gridseth, Jian Zhang, Timothy D. Barfoot

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

Rotation-Invariant Point Convolution With Multiple Equivariant Alignments.

Hugues Thomas

Proceedings of the 8th International Conference on 3D Vision, 2020

2019

Learning new representations for 3D point cloud semantic segmentation. (Apprentissage de nouvelles représentations pour la sémantisation de nuages de points 3D).

Hugues Thomas

PhD thesis, 2019

KPConv: Flexible and Deformable Convolution for Point Clouds.

Hugues Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, Leonidas J. Guibas

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods.

Hugues Thomas, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, Yann Le Gall

CoRR, 2018

Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods.

Hugues Thomas, François Goulette, Jean-Emmanuel Deschaud, Beatriz Marcotegui

Proceedings of the 2018 International Conference on 3D Vision, 2018

2016

Exploring depth information for head detection with depth images.

Siyuan Chen, François Brémond, Hung Nguyen, Hugues Thomas

Proceedings of the 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2016