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05/25/2023
SING: A Plug-and-Play DNN Learning Technique
We propose SING (StabIlized and Normalized Gradient), a plug-and-play te...
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04/14/2023
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B Imagery
High-resolution satellite imagery is a key element for many Earth monito...
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11/07/2022
Can neural networks extrapolate? Discussion of a theorem by Pedro Domingos
Neural networks trained on large datasets by minimizing a loss have beco...
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05/04/2022
Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
Modern Earth observation satellites capture multi-exposure bursts of pus...
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04/25/2022
Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?
Supervised training has led to state-of-the-art results in image and vid...
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04/23/2022
Investigating Neural Architectures by Synthetic Dataset Design
Recent years have seen the emergence of many new neural network structur...
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01/25/2021
Proba-V-ref: Repurposing the Proba-V challenge for reference-aware super resolution
The PROBA-V Super-Resolution challenge distributes real low-resolution i...
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01/06/2020
Implementation of the VBM3D Video Denoising Method and Some Variants
VBM3D is an extension to video of the well known image denoising algorit...
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05/13/2019
Joint demosaicing and denoising by overfitting of bursts of raw images
Demosaicking and denoising are the first steps of any camera image proce...
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11/30/2018
Model-blind Video Denoising Via Frame-to-frame Training
Modeling the processing chain that has produced a video is a difficult r...
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11/30/2018