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Tom Monnier

PhD student at Imagine - ENPC

6-8 Av Blaise Pascal - Cité Descartes
77455 Marne-la-Vallée, France

Email: tom dot monnier at enpc dot fr

I am a second-year PhD student in the Imagine research group at École des Ponts ParisTech (ENPC) under the supervision of Mathieu Aubry. Before that, I received my engineering degree in mathematics and computer science from Mines ParisTech in 2019.

I am interested in computer vision, machine learning and deep learning. My research currently focuses on solving computer vision tasks without manual annotations, through automatically generated data, self-supervised learning techniques or unsupervised algorithms.

News


Publications


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Representing Shape Collections with Alignment-Aware Linear Models
Romain Loiseau, Tom Monnier, Mathieu Aubry, Loïc Landrieu
arXiv 2021
paper | webpage | code | bibtex

We characterize 3D shapes as affine transformations of linear families learned without supervision, and showcase its advantages on large shape collections.

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Unsupervised Layered Image Decomposition into Object Prototypes
Tom Monnier, Elliot Vincent, Jean Ponce, Mathieu Aubry
ICCV 2021
paper | webpage | code | video | slides | bibtex

An unsupervised learning framework to decompose images into object layers modeled as transformed instances of prototypical images called sprites.

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Deep Transformation-Invariant Clustering
Tom Monnier, Thibault Groueix, Mathieu Aubry
NeurIPS 2020 (oral presentation)
paper | webpage | code | video | slides | bibtex

A simple and interpretable approach to clustering that jointly learns prototypes and prototype transformations to match data.

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docExtractor: An off-the-shelf historical document element extraction
Tom Monnier, Mathieu Aubry
ICFHR 2020 (oral presentation)
paper | webpage | code | demo | video | slides | bibtex

Leveraging synthetic data and segmentation networks for generic element extraction in real historical document images.

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A web application for watermark recognition
O. Bounou, T. Monnier, I. Pastrolin, X. Shen, C. Bénévent and others
JDMDH 2020
paper | web application | related paper (Shen et al.)

New public web application dedicated to automatic watermark recognition.

Teaching


Work experience


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Last update: September 2021