4 citations · 5 across the 9 of their papers we have counts for
12 papers · 1 filter
SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI
Álvaro Díaz-Laureano, Roger Marí, Elías Masquil +2
Accurate 3D reconstruction from satellite imagery typically relies on near-simultaneous stereo pairs, limiting its applicability to diachronic settings where multi-date images exhi…
Self-Supervised Uncertainty Estimation For Super-Resolution of Satellite Images
Zhe Zheng, Valéry Dewil, Pablo Arias
Super-resolution (SR) of satellite imagery is challenging due to the lack of paired low-/high-resolution data. Recent self-supervised SR methods overcome this limitation by exploit…
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B Imagery
Ngoc Long Nguyen, Jérémy Anger, Axel Davy +2
High-resolution satellite imagery is a key element for many Earth monitoring applications. Satellites such as Sentinel-2 feature characteristics that are favorable for super-resolu…
Can neural networks extrapolate? Discussion of a theorem by Pedro Domingos
Adrien Courtois, Jean-Michel Morel, Pablo Arias
Neural networks trained on large datasets by minimizing a loss have become the state-of-the-art approach for resolving data science problems, particularly in computer vision, image…
Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
Ngoc Long Nguyen, Jérémy Anger, Axel Davy +2
Modern Earth observation satellites capture multi-exposure bursts of push-frame images that can be super-resolved via computational means. In this work, we propose a super-resoluti…
Investigating Neural Architectures by Synthetic Dataset Design
Adrien Courtois, Jean-Michel Morel, Pablo Arias
Recent years have seen the emergence of many new neural network structures (architectures and layers). To solve a given task, a network requires a certain set of abilities reflecte…