activity
20182022
most citedReducing Anomaly Detection in Images to Detection in Noise

18 citations · 32 across the 5 of their papers we have counts for

collaborators

11 papers

cs.CV20229 cited

Detecting Methane Plumes using PRISMA: Deep Learning Model and Data Augmentation

Alexis Groshenry, Clement Giron, Thomas Lauvaux +2

The new generation of hyperspectral imagers, such as PRISMA, has improved significantly our detection capability of methane (CH4) plumes from space at high spatial resolution (30m)…

cs.CV2022

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

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. Sat-NeRF combines some of the late…

cs.CV2021

Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products

Jérémy Anger, Thibaud Ehret, Gabriele Facciolo

Recent constellations of satellites, including the Skysat constellation, are able to acquire bursts of images. This new acquisition mode allows for modern image restoration techniq…

cs.CV2020

Self-Supervised training for blind multi-frame video denoising

Valéry Dewil, Jérémy Anger, Axel Davy +3

We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. Our self-supervised approa…

cs.CV20204 cited

Implementation of the VBM3D Video Denoising Method and Some Variants

Thibaud Ehret, Pablo Arias

VBM3D is an extension to video of the well known image denoising algorithm BM3D, which takes advantage of the sparse representation of stacks of similar patches in a transform doma…

cs.CV20191 cited

Robust copy-move forgery detection by false alarms control

Thibaud Ehret

Detecting reliably copy-move forgeries is difficult because images do contain similar objects. The question is: how to discard natural image self-similarities while still detecting…