Point Cloud and 3D Modeling (NPM3D)
We created NPM3D Benchmark Suite on 3D Point Clouds: https://npm3d.fr/
Research TOPIC NPM3D
NPM3D ("Nuage de Points et Modélisation 3D") is a research topic in Centre of robotics in 3D Deep Learning on Point Clouds (from LiDAR and RGB-D sensors) for autonomous vehicles, city mapping, archeology...
Main subjects of the NMP3D research topic are:
- LiDAR SLAM
- Point cloud registration
- Scene understanging in LiDAR data: semantic segmentation, object detection
- Point cloud rendering
We have multiple 3D sensors (Kinect 2, scanner FARO Focus X130, Velodyne VLP16, HDL32) and two mobile mapping platforms:
- L3D2: vehicle with GPS/IMU localization system, Velodyne HDL32 and Ladybug5
- Drone with Velodyne VLP16 and Camera FLIR Blackfly
People
Permanent staff:
- Jean-Emmanuel Deschaud: Associate Professor, Mines Paris - PSL, jean-emmanuel.deschaud@mines-paristech.fr
External Collaborator:
- François Goulette: Full Professor, Deputy Director U2IS, ENSTA Paris, francois.goulette@ensta-paris.fr
PhD students:
- Samir Abou-Haidar (2022-): Deep neural networks on 3D point cloud adapted to embedded architectures. In collaboration with Cyril Joly and CEA LIAE lab (Alexandre Chariot and Mehdi Darouich)
- Hugo Blanc (2022-): Physico-realistic differentiable rendering of point clouds for interactive visualization of real environments, and applications to cultural heritage. In collaboration with Alexis Paljic.
- Fabio Elnecave Xavier (2022-): Odometry and 3D Reconstruction of the Close Environment of a Leg Exoskeleton. In collaboration with François Goulette and Wandercraft (Guillaume Burger and Marine Petriaux)
- Louis Soum-Fontez (2021-): Unsupervised real-time object detection from LiDAR data. In collaboration with François Goulette.
- Jules Sanchez (2020-): Real-time semantic segmentation and object detection of lidar data for the autonomous vehicle. In collaboration with François Goulette.
- Pierre Dellenbach (2020-): Self-supervised Deep SLAM on camera and LiDAR data. In collaboration with François Goulette and Kitware (Raphaël Cazorla).
Former PhD students:
- Jean-Pierre Richa (2019-2022): Urban Scene Modeling From 3D Point Clouds and Massive LiDAR Simulation for Autonomous Vehicles (working now at Outsight as R&D engineer)
- Sofiane Horache (2019-2022): Pattern comparison on 3D point clouds and application on Celtic coins and objects (working now at TheraPanacea as R&D engineer)
- David Duque (2018-2021): 3D urban scene understanding by analysis of LiDAR, color and hyperspectral data (working now in the start-up Thecrossproduct as R&D engineer)
- Hugues Thomas (2016-2019): Learning new representations for 3D point cloud semantization (now Post-Doc at University of Toronto)
- Xavier Roynard (2015-2019): On-the-fly semantization of 3D point clouds acquired by embedded systems (working now at SAFRAN as R&D engineer)
- Hassan Bouchiba (2014-2018): Contributions in point-based processing for rendering and simulation in fluid mechanics (now co-founder of the start-up Exwayz)
- Houssem Nouira (2013-2016): Point cloud refinement with self-calibration of a mobile multi-beam lidar (working now at MENSI/TRIMBLE as R&D engineer)
PUBLICATIONS






On power Jaccard losses for semantic segmentation
D. Duque-Arias, S. Velasco-Forero, J.-E. Deschaud, F. Goulette, A. Serna, E. Decencière, B. Marcotegui
VISAPP, 2021
Paper


SHREC 2020 Track: 3D Point Cloud Semantic Segmentation for Street Scenes
T. Ku, R. C. Veltkamp, B. Boom, D. Duque-Arias, S. Velasco-Forero, J.-E. Deschaud, F. Goulette, B. Marcotegui, S. Ortega, A. Trujillo, J. Pablo Suárez, J. Miguel Santana, C. Ramírez, K. Akadas, S. Gangisetty
Computer & Graphics, 2020
Paper

Computational Fluid Dynamics on 3D Point Set Surfaces
H. Bouchiba, S. Santoso, J.-E Deschaud, L. Rocha-Da-Silva, F. Goulette, T. Coupez
Journal of Computational Physics, 2020
Paper

KPConv: Flexible and Deformable Convolution for Point Clouds
H. Thomas, C. R. Qi, J.-E. Deschaud, B. Marcotegui, F. Goulette, L. J. Guibas
ICCV, 2019
Paper GitHub TensorFlow GitHub PyTorch

A Graph-based Color Lines model for image analysis
D. Duque-Arias, S. Velasco-Forero, F. Goulette, J.-E. Deschaud, B. Marcotegui
ICIAP, 2019
Paper



Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods
H. Thomas, J.-E. Deschaud, B. Marcotegui, F. Goulette, Y. Le Gall
3DV, 2018
Paper


IMLS-SLAM: scan-to-model matching based on 3D data
J.-E. Deschaud
ICRA, 2018
Paper

Point Cloud Refinement with Self-calibration of a mobile multi-beam Lidar Sensor
H. Nouira, J.-E. Deschaud, F. Goulette
The Photogrammetric Record, 2017
Paper
Current research projects
- CIFRE with Wandercraft (2022-2025): Wandercraft
- 5GMed (H2020, 2021-2024): Obstacle Detection on LiDAR data through 5G for automotive and railway cases Project Website
- CIFRE with Kitware (2021-2023): Kitware
- Research project with ANSYS (2020-2022): ANSYS