1 citations · 5 across the 10 of their papers we have counts for
11 papers
PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer
David Picard, Nicolas Dufour, Lucas Degeorge +14
This paper introduces the Polynomial Mixer (PoM), a novel token mixing mechanism with linear complexity that serves as a drop-in replacement for self-attention. PoM aggregates inpu…
Remote Sensing Change Detection via Weak Temporal Supervision
Xavier Bou, Elliot Vincent, Gabriele Facciolo +3
Semantic change detection in remote sensing aims to identify land cover changes between bi-temporal image pairs. Progress in this area has been limited by the scarcity of annotated…
CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis
Abhishek Kuriyal, Elliot Vincent, Mathieu Aubry +1
Global variations in terrain appearance raise a major challenge for satellite image analysis, leading to poor model performance when training on locations that differ from those en…
Detecting Looted Archaeological Sites from Satellite Image Time Series
Elliot Vincent, Mehraïl Saroufim, Jonathan Chemla +4
Archaeological sites are the physical remains of past human activity and one of the main sources of information about past societies and cultures. However, they are also the target…
Historical Printed Ornaments: Dataset and Tasks
Sayan Kumar Chaki, Zeynep Sonat Baltaci, Elliot Vincent +5
This paper aims to develop the study of historical printed ornaments with modern unsupervised computer vision. We highlight three complex tasks that are of critical interest to boo…
Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shift
Elliot Vincent, Jean Ponce, Mathieu Aubry
Satellite imagery plays a crucial role in monitoring changes happening on Earth's surface and aiding in climate analysis, ecosystem assessment, and disaster response. In this paper…
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…
Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach
Elliot Vincent, Jean Ponce, Mathieu Aubry
Improvements in Earth observation by satellites allow for imagery of ever higher temporal and spatial resolution. Leveraging this data for agricultural monitoring is key for addres…
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…
Unsupervised Layered Image Decomposition into Object Prototypes
Tom Monnier, Elliot Vincent, Jean Ponce +1
We present an unsupervised learning framework for decomposing images into layers of automatically discovered object models. Contrary to recent approaches that model image layers wi…