Search Results for author: Gabriele Facciolo

Found 19 papers, 6 papers with code

Fast Two-step Blind Optical Aberration Correction

no code implementations1 Aug 2022 Thomas Eboli, Jean-Michel Morel, Gabriele Facciolo

The optics of any camera degrades the sharpness of photographs, which is a key visual quality criterion.

Deblurring

NeRF, meet differential geometry!

no code implementations29 Jun 2022 Thibaud Ehret, Roger Marí, Gabriele Facciolo

Neural radiance fields, or NeRF, represent a breakthrough in the field of novel view synthesis and 3D modeling of complex scenes from multi-view image collections.

Novel View Synthesis

Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites

no code implementations CVPR 2022 Ngoc Long Nguyen, Jérémy Anger, Axel Davy, Pablo Arias, Gabriele Facciolo

Modern Earth observation satellites capture multi-exposure bursts of push-frame images that can be super-resolved via computational means.

Super-Resolution

Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?

no code implementations25 Apr 2022 Valéry Dewil, Aranud Barral, Gabriele Facciolo, Pablo Arias

In this paper, we propose a study aiming to determine which is the best approach to train denoising networks for real raw videos: supervision on synthetic realistic data or self-supervision on real data.

Denoising Video Denoising

Sat-NeRF: Learning Multi-View Satellite Photogrammetry With Transient Objects and Shadow Modeling Using RPC Cameras

no code implementations16 Mar 2022 Roger Marí, Gabriele Facciolo, Thibaud Ehret

We introduce the Satellite Neural Radiance Field (Sat-NeRF), a new end-to-end model for learning multi-view satellite photogrammetry in the wild.

Neural Rendering

Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery

no code implementations1 Mar 2021 Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis, Gabriele Facciolo

The refined RPCs are then used to reconstruct multiple consistent Digital Surface Models (DSMs) from different stereo pairs at each date.

Time Series

Robust Rational Polynomial Camera Modelling for SAR and Pushbroom Imaging

2 code implementations26 Feb 2021 Roland Akiki, Roger Marí, Carlo de Franchis, Jean-Michel Morel, Gabriele Facciolo

The Rational Polynomial Camera (RPC) model can be used to describe a variety of image acquisition systems in remote sensing, notably optical and Synthetic Aperture Radar (SAR) sensors.

Proba-V-ref: Repurposing the Proba-V challenge for reference-aware super resolution

1 code implementation25 Jan 2021 Ngoc Long Nguyen, Jérémy Anger, Axel Davy, Pablo Arias, Gabriele Facciolo

We argue that in doing so, the challenge ranks the proposed methods not only by their MISR performance, but mainly by the heuristics used to guess which image in the series is the most similar to the high-resolution target.

Image Super-Resolution

Residual Learning for Effective joint Demosaicing-Denoising

no code implementations14 Sep 2020 Yu Guo, Qiyu Jin, Gabriele Facciolo, Tieyong Zeng, Jean-Michel Morel

Moreover, it is very difficult to change this order, because once the image is demosaicked, the statistical properties of the noise will be changed dramatically.

Demosaicking Denoising

A Review of an Old Dilemma: Demosaicking First, or Denoising First?

no code implementations24 Apr 2020 Qiyu Jin, Gabriele Facciolo, Jean-Michel Morel

In this paper, we review the main variants of these strategies and carry-out an extensive evaluation to find the best way to reconstruct full color images from a noisy mosaic.

Demosaicking Image Denoising

Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw Images

1 code implementation ICCV 2019 Thibaud Ehret, Axel Davy, Pablo Arias, Gabriele Facciolo

Due to the unavailability of ground truth data these networks cannot be currently trained using real RAW images.

Demosaicking Denoising

Efficient Blind Deblurring under High Noise Levels

1 code implementation19 Apr 2019 Jérémy Anger, Mauricio Delbracio, Gabriele Facciolo

In this work, we first show that current state-of-the-art kernel estimation methods based on the $\ell_0$ gradient prior can be adapted to handle high noise levels while keeping their efficiency.

Blind Image Deblurring Denoising +1

Assessing the Sharpness of Satellite Images: Study of the PlanetScope Constellation

no code implementations19 Apr 2019 Jérémy Anger, Carlo de Franchis, Gabriele Facciolo

New micro-satellite constellations enable unprecedented systematic monitoring applications thanks to their wide coverage and short revisit capabilities.

Model-blind Video Denoising Via Frame-to-frame Training

1 code implementation CVPR 2019 Thibaud Ehret, Axel Davy, Jean-Michel Morel, Gabriele Facciolo, Pablo Arias

Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available.

Denoising Video Denoising

Non-Local Video Denoising by CNN

2 code implementations30 Nov 2018 Axel Davy, Thibaud Ehret, Jean-Michel Morel, Pablo Arias, Gabriele Facciolo

To the best of our knowledge, this is the first successful application of a CNN to video denoising.

Image Denoising Video Denoising

Modeling Realistic Degradations in Non-blind Deconvolution

no code implementations4 Jun 2018 Jérémy Anger, Mauricio Delbracio, Gabriele Facciolo

We show that accurately modeling a more realistic image acquisition pipeline leads to significant improvements, both in terms of image quality and PSNR.

Deblurring Image Deblurring +2

Accurate Motion Estimation through Random Sample Aggregated Consensus

no code implementations19 Jan 2017 Martin Rais, Gabriele Facciolo, Enric Meinhardt-Llopis, Jean-Michel Morel, Antoni Buades, Bartomeu Coll

This yields RANSAAC, a framework that improves systematically over RANSAC and its state-of-the-art variants by statistically aggregating hypotheses.

Motion Estimation

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