About
Experiences
Education
Publication
Projects

About

I am an aspiring Computer Vision researcher, and I am extremely lucky to be working with Prof. Vincent Sitzmann as a visiting student in the Scene Representation Group at MIT CSAIL. In a few words, the vision that I pursue through my research is the development of Perception systems that can learn from minimal supervision by drawing inspiration from first principles.

In the past, I have been lucky to collaborate with and learn from fantastic researchers to start advancing towards this goal. I have spent a summer collaborating with Prof. Jia Deng in the Princeton Vision & Learning Lab, where I investigated 4D reconstruction from videos of highly-dynamic scenes. I have also spent a wonderful summer working with Prof. Mathieu Aubry in the Imagine team at ENPC, working on weakly-supervised learning of visual prototypes with applications to document analysis.

News

Sep. 2024 - The Learnable Typewriter won the Best paper award at ICDAR 2024, kudos Ioannis!

Mar. 2024 - The Learnable Typewriter - our paper on document analysis using weak or no supervision - has been accepted to ICDAR 2024!

Feb. 2024 - Excited to start my visiting stay with Prof. Vincent Sitzmann in the Scene Representation Group!

Sep. 2023 - I obtained the Master MVA from École Normale Supérieure Paris-Saclay!

Research experiences

Feb. 2024 - Present
Visiting student working with Prof. Vincent Sitzmann in the Scene Representation Group at MIT CSAIL.

May - Sep. 2023
Master's Thesis advised by Prof. Jia Deng in the Princeton Vision & Learning Lab.
Subject: 3D Vision, Scene Representation.

Apr. - Sep. 2022
Research internship advised by Prof. Mathieu Aubry in the Imagine team at ENPC.
Subject: Weakly-supervised methods for analysis of Text-line images.

May. - Aug. 2021
Research internship advised by Prof. Emmanuel Dellandrea at CNRS LIRIS.
Subject: Real-time Visual Scene Understanding for Robotics.

Education

2022 - 2023
Master's Degree Mathematics, Vision and Learning (MVA) at ENS Paris-Saclay

2019 - 2022
French Engineering degree (=M.Sc.) in Applied Mathematics at École Centrale de Lyon

I am also passionate about Mathematics! I pursued a double-curriculum with Lyon 1 University during my engineering studies, getting a B.Sc. in Mathematics and an M.Sc in Applied Mathematics.

Publication

The Learnable Typewriter: A Generative Approach to Text Analysis

I. Siglidis, N. Gonthier, J. Gaubil, T. Monnier, M. Aubry
ICDAR 2024   ⭐ Best Paper Award
Webpage    arXiv     Code

We introduce a generative approach for character analysis and recognition in text line images that can perform using little to no supervision.

Projects

Here are listed some course projects that I enjoy sharing and that are representative of my past and current research interests.


Self-Supervised Learning of Visual Representations

  Report
MVA, Computer Vision course  with Manh-Dan Pham. 

Study of the recently proposed VICReg and SimCLR, evaluation of the representations learned by VICReg on a challenging downstream task of Fine-grained image Classification and in a small dataset setting.


Weakly-supervised analysis of text-line images

  Code     Report
MVA, Deep Learning course.

Developments of the Learnable Typewriter, using several learned prototypes per character instead of a single one, which then made it to the final paper. Design of a richer transformation scheme by using Thin Plate Spline transformations.


Neural Point-based rendering and View Synthesis

  Report
MVA, Point Cloud and 3D Modelling course.

Study of the point-based Scene Representation Scuplted Neural Points. Evaluation of the proposed sculpting mechanism, ablation study and proposition of improvements.


Gamma Denoising Diffusion Implicit Models

  Report
MVA, Generative Models for Images course  with Thomas Dujardin, Thibault Richard.

Study of Denoising Diffusion Implicit Models, drawing parallels with Deep Equilibrium models, experimenting with different subsampling methods and proposing an - at the time - first derivation of the backward process for Gamma-DDIMs.