no code implementations • 31 Mar 2023 • Agapius Bou Ghosn, Philip Polack, Arnaud de La Fortelle
This model is also used in an Extended Kalman Filter (EKF) for comparison of the learning-based observer with a state of the art model-based observer.
no code implementations • ICCV 2023 • Arthur Moreau, Nathan Piasco, Moussab Bennehar, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle
Beyond novel view synthesis, Neural Radiance Fields are useful for applications that interact with the real world.
no code implementations • 9 Feb 2023 • Richard Schubert, Marcus Nolte, Arnaud de La Fortelle, Markus Maurer
Hence, the quality of the underlying models has to be evaluated with respect to the ODD.
1 code implementation • 26 May 2022 • Bruno Sauvalle, Arnaud de La Fortelle
We introduce a new architecture for unsupervised object-centric representation learning and multi-object detection and segmentation, which uses a translation-equivariant attention mechanism to predict the coordinates of the objects present in the scene and to associate a feature vector to each object.
Ranked #1 on Unsupervised Object Segmentation on ClevrTex
no code implementations • 5 May 2022 • Arthur Moreau, Thomas Gilles, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle
We propose a novel learning-based formulation for visual localization of vehicles that can operate in real-time in city-scale environments.
1 code implementation • 15 Dec 2021 • Bruno Sauvalle, Arnaud de La Fortelle
The main novelty of the proposed model is that the autoencoder is also trained to predict the background noise, which allows to compute for each frame a pixel-dependent threshold to perform the foreground segmentation.
no code implementations • 13 Oct 2021 • Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle
Neural Radiance Fields (NeRF) have recently demonstrated photo-realistic results for the task of novel view synthesis.
no code implementations • 19 Mar 2021 • Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle
In this setup, structure-based methods require a large database, and we show that our proposal is a reliable alternative, achieving 29cm median error in a 1. 9km loop in a busy urban area
Ranked #2 on Camera Localization on Oxford RobotCar Full
no code implementations • 30 Sep 2019 • Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, Masayoshi Tomizuka
3) The driving behavior is highly interactive and complex with adversarial and cooperative motions of various traffic participants.
no code implementations • 31 Jul 2019 • Michelle Valente, Cyril Joly, Arnaud de La Fortelle
Cameras and 2D laser scanners, in combination, are able to provide low-cost, light-weight and accurate solutions, which make their fusion well-suited for many robot navigation tasks.
no code implementations • 4 Jun 2019 • Salma Benslimane, Simon Tamayo, Arnaud de La Fortelle
Major cities can use traffic counting as a tool to monitor the presence of delivery vehicles in order to implement intelligent city planning measures.
no code implementations • 22 Feb 2019 • Michelle Valente, Cyril Joly, Arnaud de La Fortelle
The use of 2D laser scanners is attractive for the autonomous driving industry because of its accuracy, light-weight and low-cost.
Robotics
no code implementations • 24 Jan 2018 • Florent Altché, Arnaud de La Fortelle
In order to drive safely and efficiently on public roads, autonomous vehicles will have to understand the intentions of surrounding vehicles, and adapt their own behavior accordingly.
no code implementations • 5 Apr 2017 • Philip Polack, Brigitte d'Andréa-Novel, Michel Fliess, Arnaud de La Fortelle, Lghani Menhour
This communication presents a longitudinal model-free control approach for computing the wheel torque command to be applied on a vehicle.