Thibaud Ehret

I am currently a post-doc at the Centre Borelli at ENS Paris-Saclay, where I work on anomaly detection and different projects linked with remote sensing.

I did my PhD at the CMLA at ENS Cachan, where I was advised by Jean-Michel Morel.

Email / GitHub / Google Scholar

Research

I'm interested in image and video processing, optimization and remote sensing.

	Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery Thibaud Ehret, Aurélien De Truchis, Matthieu Mazzolini, Jean-Michel Morel, Alexandre d'Aspremont, Thomas Lauvaux, Gabriele Facciolo ACS, 2022 paper / A study of super-emission of methane emissions related to oil and gas in the world.
	NeRF, meet differential geometry! Thibaud Ehret, Roger Marí, Gabriele Facciolo Preprint, 2022 paper / Introducing differential geometry tools to NeRFs.
	L1B+: A Perfect Sensor Localization Model for Simple Satellite Stereo Reconstruction From Push-frame Image Strips Roger Marí, Thibaud Ehret, Jérémy Anger, Carlo de Franchis, Gabriele Facciolo ISPRS 2022, 2022 paper / We emulates a perfect sensor to generate a single image strip from multiple image push-frame strips.
	Sat-NeRF: Learning Multi-View Satellite Photogrammetry With Transient Objects and Shadow Modeling Using RPC Cameras Roger Marí, Gabriele Facciolo, Thibaud Ehret CVPRW 2022, 2022 paper / code / NeRF for 3D modeling of satellite scenes. Project page: https://centreborelli.github.io/satnerf/
	Video Denoising by Combining Patch Search and CNNs Axel Davy, Thibaud Ehret, Jean-Michel Morel, Pablo Arias, Gabriele Facciolo JMIV, 2021 paper / code / Video denoising using CNN and non-locality.
	Image anomalies: A review and synthesis of detection methods Thibaud Ehret, Axel Davy, Mauricio Delbracio, Jean-Michel Morel JMIV, 2019 paper / code / A study of anomaly detection in images.
	Joint Demosaicking and denoising by fine-tuning of bursts of raw images Thibaud Ehret, Axel Davy, Pablo Arias, Gabriele Facciolo ICCV 2019, 2019 paper / code / poster / Self-supervised learning of joint demosaicking and denoising using only raw bursts.
	Model-blind video denoising via frame-to-frame training Thibaud Ehret, Axel Davy, Jean-Michel Morel, Gabriele Facciolo, Pablo Arias CVPR 2019, 2019 paper / code / poster / A model-blind video denoising method based on online learning from a single video.
	Non-local kalman: A recursive video denoising algorithm Thibaud Ehret, Jean-Michel Morel, Pablo Arias ICIP 2018, 2018 paper / poster / We propose a new recursive video denoising method combining non-local denoising principles with recursive video denoising. Project website with video examples: https://tehret.github.io/nlkalman/
	On the convergence of PatchMatch and its variants Thibaud Ehret, Pablo Arias CVPR 2018, 2018 paper / poster / A theoretical analysis of PatchMatch.
	Global patch search boosts video denoising Thibaud Ehret, Pablo Arias, Jean-Michel Morel VISAPP 2017, 2017 paper / We study the impact of the local search in patch-based video denoising and show how a global search can improve the quality of the result.