Vincent Nozick
Associate Professor at Université Gustave Eiffel.Laboratoire d'informatique Gaspard Monge (LIGM).
In charge of Master 2 sciences de l'image.
Contact
email : vincent.nozick (a) univ-eiffel.fr address : Laboratoire d'informatique Gaspard Monge Université Gustave Eiffel Cite DESCARTES, 5 boulevard Descartes 77454 Marne-la-Vallée CEDEX 2 France phone number : ESIEE (office 5357): 01 45 92 67 03 |
Research
- Geometric algebra
- Computer vision
- Digital image forensics
Professional background
- 2019 : Habilitation a diriger les recherches (HDR)
- since 2008: Maître de conferences (associate professor) : Université Gustave Eiffel, LIGM-A3SI, France
- 2016-2018: sabbatical at JFLI, Tokyo, Japan
- 2016-2018: invited researcher at Hideo Saito Lab, Keio University, Japan
- 2011-2013: Headmaster of IMAC engineer school
- 2007-2008: Research Associate : Keio University, Japan
- 2006-2007: Post-doc : Hideo Saito lab, Keio University, Japan
- 2002-2006: PhD degree in computer sciences
Geometric algebra and Garamon
Garamon stands for Geometric Algebra Recursive and Adaptative Monster. It is a C++ library generator synthesizing efficient C++ libraries implementing geometric algebras in both low and higher dimensions, with any arbitrary metric. The library generator is designed to produce easy to install, easy to use, effective and numerically stable libraries. The design of the libraries is based on a prefix tree data structure and a recursive scheme for high dimensions.The source code is available online:
- git clone https://github.com/vincentnozick/garamon.git
- pre-print: breuils_AGACSE_2018.pdf
- slides: garamon.pdf
MesoNet: a Compact Facial Video Forgery Detection Network
MesoNet is a deep learning program dedicated to to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face.MesoNet: a Compact Facial Video Forgery Detection Network, Darius Afchar, Vincent Nozick, Junichi Yamagishi and Isao Echizen, in IEEE Workshop on Information Forensics and Security, WIFS, December 2018.
- paper: MesoNet_WIFS_2018.pdf on arxiv
- source code: MesoNet (git)
Computer graphics vs. photgraphic images
This paper presents a method to distinguish computer graphics from real photographic images. The program is based on a convolution neural network focussing on the statistical properties of the images, including image noise, to efficiently classify the data.Distinguishing Computer Graphics from Natural Images Using Convolution Neural Networks, Nicolas Rahmouni, Vincent Nozick, Junichi Yamagishi and Isao Echizen, in IEEE Workshop on Information Forensics and Security, WIFS 2017, Rennes, France, December 2017.
- pdf: Rahmouni_WIFS_2017.pdf
- source code: CGvsPhoto (git)
- dataset: GameCG.zip
Press
TV
- M6 info : le 19.45 du 12 Octobre 2019
- M6 info : le 12.45 du 12 mars 2019
- BFMTV : lundi 1er Juillet 2019
- Public Senat : Hashtag l'émission du 16 Janvier 2020
Radio
- France Culture : la méthode scientifique
- France Culture : la question du jour (video).
Youtube
Pres on the web
- Le Monde.fr / Universcience.tv
- Sciences et Avenir
- France24
- Le Figaro.fr
- L'OBS (AFP)
- L'express - l'expansion (AFP)
- Le journal du geek
- Hello Future
- Les eclaireurs de la com
- La gazette de Paris
- Gralon
- Choose Your Boss
- The world news
- Ultimate Pocket
- Technikart
- Notre temps (AFP)
Written press
- Le Monde
- DNA
- Sciences & vie
- Science et Avenir, Hors serie Octobre-Novembre 2019, p.44-45
- Le Figaro
International
- 日経サイエンス 2019年1月号
- 科学新聞
- 読売新聞
- 日刊工業新聞 電子版
- ニュ-スイッチ
- RFI espanol
- AFRIC
- Teller Report (AFP)
- Mundobit (AFP)