6 citations · 9 across the 7 of their papers we have counts for
9 papers
ABM: Alignment-Aware Bridge Matching for Image-to-Image Translation
Aimi Okabayashi, Georges Le Bellier, Nicolas Audebert +3
Paired image-to-image translation underpins a wide range of computer vision tasks, including image editing, sensor translation, and domain adaptation. Bridge matching and flow matc…
FlowEO: Generative Unsupervised Domain Adaptation for Earth Observation
Georges Le Bellier, Nicolas Audebert
The increasing availability of Earth observation data offers unprecedented opportunities for large-scale environmental monitoring and analysis. However, these datasets are inherent…
3DSES: an indoor Lidar point cloud segmentation dataset with real and pseudo-labels from a 3D model
Maxime Mérizette, Nicolas Audebert, Pierre Kervella +1
Semantic segmentation of indoor point clouds has found various applications in the creation of digital twins for robotics, navigation and building information modeling (BIM). Howev…
PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models
Valerio Marsocci, Yuru Jia, Georges Le Bellier +12
Geospatial Foundation Models (GFMs) have emerged as powerful tools for extracting representations from Earth observation data, but their evaluation remains inconsistent and narrow.…
Improved symbolic drum style classification with grammar-based hierarchical representations
Léo Géré, Philippe Rigaux, Nicolas Audebert
Deep learning models have become a critical tool for analysis and classification of musical data. These models operate either on the audio signal, e.g. waveform or spectrogram, or…
GalLoP: Learning Global and Local Prompts for Vision-Language Models
Marc Lafon, Elias Ramzi, Clément Rambour +2
Prompt learning has been widely adopted to efficiently adapt vision-language models (VLMs), e.g. CLIP, for few-shot image classification. Despite their success, most prompt learnin…
Cross-sensor self-supervised training and alignment for remote sensing
Valerio Marsocci, Nicolas Audebert
Large-scale ''foundation models'' have gained traction as a way to leverage the vast amounts of unlabeled remote sensing data collected every day. However, due to the multiplicity…
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time series
Aimi Okabayashi, Nicolas Audebert, Simon Donike +1
Satellite imaging generally presents a trade-off between the frequency of acquisitions and the spatial resolution of the images. Super-resolution is often advanced as a way to get…
Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models
Georges Le Bellier, Nicolas Audebert
Earth Observation imagery can capture rare and unusual events, such as disasters and major landscape changes, whose visual appearance contrasts with the usual observations. Deep mo…