Tom Monnier

PhD student at Imagine - ENPC

I am a final-year PhD candidate (graduation: Summer 2023) advised by Mathieu Aubry at ENPC. During my PhD, I was fortunate to work with Jean Ponce (Inria), Matthew Fisher (Adobe Research), Alyosha Efros and Angjoo Kanazawa (UC Berkeley). Before that, I completed my engineer's degree (=M.Sc.) at Mines Paris.

My research focuses on building machines that learn to perceive our visual world without any annotations, through self-supervised and unsupervised learning techniques. Representative papers are highlighted.

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03 / 2023 Our work MACARONS on simultaneous path planning and 3D reconstruction has been accepted to CVPR 2023!
02 / 2023 The Learnable Typewriter - a document-analysis system learned with no or weak supervision - is published on arXiv
12 / 2022 Our analytical paper on unsupervised visual reasoning has been accepted at NeurIPS 2022 SSL Workshop!
07 / 2022 The single-view reconstruction method UNICORN 🦄 has been accepted to ECCV 2022!
06 / 2022 Visiting University of California and presenting my PhD work at Berkeley AI Research
10 / 2021 Our work on representing 3D shapes has been accepted at 3DV 2021!
07 / 2021 Our sprite-based image decomposition approach has been accepted to ICCV 2021!
05 / 2021 Starting a remote internship in the Creative Intelligence Lab at Adobe Research advised by Matthew Fisher
12 / 2020 Presenting DTI Clustering at a workshop for ParisMLGroup
11 / 2020 Presenting docExtractor at a DHNord 2020 workshop
10 / 2020 Our work on DTI Clustering is accepted at NeurIPS 2020 as an oral presentation!
06 / 2020 Our system docExtractor is accepted at ICFHR 2020 as an oral!
02 / 2020 Starting PhD in the Imagine research group at ENPC under the supervision of Mathieu Aubry
01 / 2020 Our web application for watermark recognition is online, check out the paper and test the app here!

Publications

We introduce MACARONS, a method that learns in a self-supervised fashion to explore new environments and reconstruct them in 3D using RGB images only.

The Learnable Typewriter: A Generative Approach to Text Line Analysis
Ioannis Siglidis, Nicolas Gonthier, Julien Gaubil, Tom Monnier, Mathieu Aubry
arXiv 2023
paper | webpage | code | bibtex

We build upon sprite-based image decomposition approaches to design a generative method for character analysis and recognition in text lines.

Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason?
Monika Wysoczanska, Tom Monnier, Tomasz Trzcinski, David Picard
NeurIPS Workshops 2022
paper | bibtex

A Transformer-based framework to evaluate off-the-shelf features (object-centric and dense representations) for the reasoning task of VQA.

We present UNICORN 🦄, a self-supervised approach leveraging the consistency across different single-view images for high-quality 3D reconstructions.

Representing Shape Collections with Alignment-Aware Linear Models
Romain Loiseau, Tom Monnier, Mathieu Aubry, Loïc Landrieu
3DV 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.

We discover the objects recurrent in unlabeled image collections by modeling images as a composition of learnable sprites.

A simple adaptation of K-means to make it work on pixels! We align prototypes to each sample image before computing cluster distances.

Leveraging synthetic training data to efficiently extract visual elements from historical document images.

Academic activities

Visiting student, University of California, Berkeley (USA) July 2022

Research intern, Adobe Research, San Francisco (USA, remote), Summer 2021

Teaching assistant, DEEPL (Masters level) at ENPC, Fall 2020 and Spring 2021

Reviewer: MVA 2021, ICCV 2021, NeurIPS 2021, ECCV 2022, CVPR 2023, ICCV 2023, NeurIPS 2023

Open source projects:

unicorn docExtractor dti-clustering dti-sprites webpage

Invited talks

07 / 2022 Seminar, BAIR - University of California, Berkeley (USA)

04 / 2022 Seminar, Imagine - ENPC, La Turballe (France)

03 / 2021 Seminar, DHAI - Ecole Normale Supérieure, Paris (France, virtual)

02 / 2021 Seminar, LIGM - ESIEE, Paris (France)

12 / 2020 Workshop, Paris Machine Learning Group, Paris (France, virtual)

12 / 2020 Conference oral, NeurIPS 2020, Vancouver (Canada, virtual)

11 / 2020 Workshop, DHNord 2020, Lille (France, virtual)

09 / 2020 Conference oral, ICFHR 2020, Dortmund (Germany, virtual)