97 citations · 217 across the 23 of their papers we have counts for
27 papers
Robust RPC Bundle Adjustment for Multi-Date Satellite Imagery with Season-Invariant Correspondences
Roger Marí, Elías Masquil, Xavier Bou +2
Accurate refinement of Rational Polynomial Camera (RPC) models is essential for high-quality satellite image geolocation. In ground control point (GCP)-free multi-view pipelines, t…
Deep S2P: Integrating Learning Based Stereo Matching Into the Satellite Stereo Pipeline
Elías Masquil, Thibaud Ehret, Pablo Musé +1
Digital Surface Model generation from satellite imagery is a core task in Earth observation and is commonly addressed using classical stereoscopic matching algorithms in satellite…
An Industrial Dataset for Scene Acquisitions and Functional Schematics Alignment
Flavien Armangeon, Thibaud Ehret, Enric Meinhardt-Llopis +4
Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Cu…
Diachronic Stereo Matching for Multi-Date Satellite Imagery
Elías Masquil, Luca Savant Aira, Roger Marí +3
Recent advances in image-based satellite 3D reconstruction have progressed along two complementary directions. On one hand, multi-date approaches using NeRF or Gaussian-splatting j…
Remote Sensing Change Detection via Weak Temporal Supervision
Xavier Bou, Elliot Vincent, Gabriele Facciolo +3
Semantic change detection in remote sensing aims to identify land cover changes between bi-temporal image pairs. Progress in this area has been limited by the scarcity of annotated…
EOGS++: Earth Observation Gaussian Splatting with Internal Camera Refinement and Direct Panchromatic Rendering
Pierrick Bournez, Luca Savant Aira, Thibaud Ehret +1
Recently, 3D Gaussian Splatting has been introduced as a compelling alternative to NeRF for Earth observation, offering competitive reconstruction quality with significantly reduce…
Towards Large Scale Geostatistical Methane Monitoring with Part-based Object Detection
Adhemar de Senneville, Xavier Bou, Thibaud Ehret +5
Object detection is one of the main applications of computer vision in remote sensing imagery. Despite its increasing availability, the sheer volume of remote sensing data poses a…
S-EO: A Large-Scale Dataset for Geometry-Aware Shadow Detection in Remote Sensing Applications
Elías Masquil, Roger Marí, Thibaud Ehret +3
We introduce the S-EO dataset: a large-scale, high-resolution dataset, designed to advance geometry-aware shadow detection. Collected from diverse public-domain sources, including…
Gaussian Splatting for Efficient Satellite Image Photogrammetry
Luca Savant Aira, Gabriele Facciolo, Thibaud Ehret
Recently, Gaussian splatting has emerged as a strong alternative to NeRF, demonstrating impressive 3D modeling capabilities while requiring only a fraction of the training and rend…
Structure Tensor Representation for Robust Oriented Object Detection
Xavier Bou, Gabriele Facciolo, Rafael Grompone von Gioi +2
Oriented object detection predicts orientation in addition to object location and bounding box. Precisely predicting orientation remains challenging due to angular periodicity, whi…
Exploring Robust Features for Few-Shot Object Detection in Satellite Imagery
Xavier Bou, Gabriele Facciolo, Rafael Grompone von Gioi +2
The goal of this paper is to perform object detection in satellite imagery with only a few examples, thus enabling users to specify any object class with minimal annotation. To thi…
Portraying the Need for Temporal Data in Flood Detection via Sentinel-1
Xavier Bou, Thibaud Ehret, Rafael Grompone von Gioi +1
Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been…
Radar Fields: An Extension of Radiance Fields to SAR
Thibaud Ehret, Roger Marí, Dawa Derksen +2
Radiance fields have been a major breakthrough in the field of inverse rendering, novel view synthesis and 3D modeling of complex scenes from multi-view image collections. Since th…
Reducing False Alarms in Video Surveillance by Deep Feature Statistical Modeling
Xavier Bou, Aitor Artola, Thibaud Ehret +3
Detecting relevant changes is a fundamental problem of video surveillance. Because of the high variability of data and the difficulty of properly annotating changes, unsupervised m…
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)…
Regularization of NeRFs using differential geometry
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. Numerous recent…
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…
Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery
Thibaud Ehret, Aurélien De Truchis, Matthieu Mazzolini +6
Methane (CH4) emissions estimates from top-down studies over oil and gas basins have revealed systematic under-estimation of CH4 emissions in current national inventories. Sparse b…
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…
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…
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…
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…
Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw Images
Thibaud Ehret, Axel Davy, Pablo Arias +1
Demosaicking and denoising are the first steps of any camera image processing pipeline and are key for obtaining high quality RGB images. A promising current research trend aims at…
Reducing Anomaly Detection in Images to Detection in Noise
Axel Davy, Thibaud Ehret, Jean-Michel Morel +1
Anomaly detectors address the difficult problem of detecting automatically exceptions in an arbitrary background image. Detection methods have been proposed by the thousands becaus…