Detecting relevant changes is a fundamental problem of video surveillanc...
Even though data annotation is extremely important for interpretability,...
Blurry images usually exhibit similar blur at various locations across t...
We propose SING (StabIlized and Normalized Gradient), a plug-and-play
te...
Neural style transfer is a deep learning technique that produces an
unpr...
Neural networks trained on large datasets by minimizing a loss have beco...
The optics of any camera degrades the sharpness of photographs, which is...
Recent years have seen the emergence of many new neural network structur...
The Rational Polynomial Camera (RPC) model can be used to describe a var...
Image demosaicing and denoising are key steps for color image production...
Silhouettes or 2D planar shapes are extremely important in human
communi...
Image denoising and demosaicking are the most important early stages in
...
Anomaly detectors address the difficult problem of detecting automatical...
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...
This paper introduces a quantitative evaluation of filters that seek to
...
We review the broad variety of methods that have been proposed for anoma...
Many psychophysical studies are dedicated to the evaluation of the human...
Exemplar-based texture synthesis is the process of generating, from an i...
We reconsider the classic problem of estimating accurately a 2D
transfor...
In this paper, we reconsider the early computer vision bottom-up program...
The most popular image matching algorithm SIFT, introduced by D. Lowe a
...
Most computer vision application rely on algorithms finding local
corres...
This paper addresses the high precision measurement of the distortion of...
This paper introduces a statistical method to decide whether two blocks ...