1 citations · 2 across the 5 of their papers we have counts for
6 papers
Deep Sprite-based Image Models: An Analysis
Zeynep Sonat Baltacı, Romain Loiseau, Mathieu Aubry
While foundation models drive steady progress in image segmentation and diffusion algorithms compose always more realistic images, the seemingly simple problem of identifying recur…
OpenStreetView-5M: The Many Roads to Global Visual Geolocation
Guillaume Astruc, Nicolas Dufour, Ioannis Siglidis +10
Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms. Yet, the absence of…
Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans
Romain Loiseau, Elliot Vincent, Mathieu Aubry +1
We propose an unsupervised method for parsing large 3D scans of real-world scenes with easily-interpretable shapes. This work aims to provide a practical tool for analyzing 3D scen…
A Model You Can Hear: Audio Identification with Playable Prototypes
Romain Loiseau, Baptiste Bouvier, Yann Teytaut +3
Machine learning techniques have proved useful for classifying and analyzing audio content. However, recent methods typically rely on abstract and high-dimensional representations…
Online Segmentation of LiDAR Sequences: Dataset and Algorithm
Romain Loiseau, Mathieu Aubry, Loïc Landrieu
Roof-mounted spinning LiDAR sensors are widely used by autonomous vehicles. However, most semantic datasets and algorithms used for LiDAR sequence segmentation operate on $360^\cir…
Representing Shape Collections with Alignment-Aware Linear Models
Romain Loiseau, Tom Monnier, Mathieu Aubry +1
In this paper, we revisit the classical representation of 3D point clouds as linear shape models. Our key insight is to leverage deep learning to represent a collection of shapes a…