Detecting relevant changes is a fundamental problem of video surveillanc...
This work proposes a strategy for training models while annotating data ...
Even though data annotation is extremely important for interpretability,...
Blurry images usually exhibit similar blur at various locations across t...
High-resolution satellite imagery is a key element for many Earth monito...
Image resolution is an important criterion for many applications based o...
In this work, we study the problem of single-image super-resolution (SIS...
Self-supervised representation learning based on Contrastive Learning (C...
The optics of any camera degrades the sharpness of photographs, which is...
Neural radiance fields, or NeRF, represent a breakthrough in the field o...
Modern Earth observation satellites capture multi-exposure bursts of
pus...
Supervised training has led to state-of-the-art results in image and vid...
We introduce the Satellite Neural Radiance Field (Sat-NeRF), a new end-t...
This paper proposes a system for automatic surface volume monitoring fro...
The Rational Polynomial Camera (RPC) model can be used to describe a var...
Recent constellations of satellites, including the Skysat constellation,...
The PROBA-V Super-Resolution challenge distributes real low-resolution i...
Image demosaicing and denoising are key steps for color image production...
Image denoising and demosaicking are the most important early stages in
...
Demosaicking and denoising are the first steps of any camera image proce...
New micro-satellite constellations enable unprecedented systematic monit...
The goal of blind image deblurring is to recover a sharp image from a mo...
Modeling the processing chain that has produced a video is a difficult
r...
Non-local patch based methods were until recently state-of-the-art for i...
Most image deblurring methods assume an over-simplistic image formation ...
We reconsider the classic problem of estimating accurately a 2D
transfor...