Geometric & Visual Computing


New: We have several new open positions: Three Master internships opening on Computer Vision, Animation and Geometry, one PhD in learning, and one PostDoc with a company: Check our Job Offers page.

Short Description

Geometric & Visual Computing (GeoViC) is a Computer Graphics and Computer Vision group tackling geometric analysis, modeling and computer animation research.

The team is part of the "Modeling, Simulation & Learning" pole of the LIX (Laboratoire d'Informatique de l'Ecole Polytechnique) in Palaiseau.
It depends of the CNRS and Ecole Polytechnique, IP Paris.

> See slides presenting our Team


  • Computer Graphics
  • Computer Vision
  • Computer Animation
  • Expressive Modeling (Creative AI)
  • Geometry Processing and Shape Analysis
  • Implicit surfaces
  • Interactive Shape Design
  • Interaction with virtual contents
  • Machine Learning applied to visual and geometric data
  • Natural phenomena
  • Procedural Modeling
  • Visual Simulation
  • Scientific Visualization

Research methodology and applications

Our approach favors the introduction of efficient structures for high-level, possibly abstract, geometrical features of the studied shapes or phenomena. These structures can either be extracted from existing data or synthesized from prior knowledge and mathematical modeling.

Examples of such structures span latent space obtained from geometric-aware convolutional neural networks, distributions of shape arrangements and their associated metric, intrinsic properties on manifolds such as local-symmetry or Gaussian curvature, non-manifold skeletal structures representing volumetric implicit shapes, visual surface features associated with details or wrinkles on a parent shape, multi-resolution representations of complex shapes, as well as space-time features expressing user-guided or simulated interactions such as contacts and shape deformations.

These structures offer an efficient computational representation highlighting meaningful properties of the digital model and can be used to improve geometry processing algorithms, to provide support for expressive modeling or visualization methods, or to enable efficient and controllable animation.

The results of our research lead to fast and robust virtual content analysis and creation methods such as shape matching and feature retrieval, creative prototyping and modeling of detailed objects or characters that automatically adapt to the context and the user interactions, or either animated natural scenes composed of multiple layers coupling geometrical constraints with efficient simulation. The targeted applications include entertainment & artistic creation (animation cinema, video games, VFX), virtual prototyping & manufacturing, as well as modeling & visualization for natural sciences.

Main ongoing industrial chairs and grants

ERC Research Grant EXPROTEA to explore relations in structured data with functional maps.
Grant holder: Maks Ovsjanikov
H2020 Innovative Training Networks CLIPE.
Participants: Marie-Paule Cani, Pooran Memari, Damien Rohmer
Chair with Google to develop academic and research projects in IA & Visual Computing.
Chair holder: Marie-Paule Cani
Contribution to a chair with Uber to develop research projects related to visual simulation of flying taxis.
Contact in the team: Marie-Paule Cani
Contribution to a chair with Ubisoft to develop academic and research projects related to video games.
Contact in the team: Damien Rohmer

Latest events (go to events page)

January 2021

We are happy to welcome Mathieu Desbrun, currently on leave from Caltech, and joining the lab as an Inria senior researcher. We are eager to work with him in the near future, as well as working toward a reshaping of our team.

Congratulation to Mathieu Desbrun who is nominated as ACM fellow.

Congratulation to Thomas Buffet who succesfully defended his PhD (2021/01/13) on the Topic: “Field-based approaches for the collision-free animation of layered and dynamic clothing”.

December 2020

Congratulation to Pierre Ecormier-Nocca who succesfully defended his PhD (2020/12/03) on the Topic: “Authoring consistent, animated ecosystems: Efficient learning from partial data”.

November 2020

Congratulation to Renaud Chabrier who succesfully defended his PhD (2020/11/27) on the Topic: “La géométrie de la vie: quand le dessin rencontre les sciences du vivant”.

September 2020

We are happy to welcome Vicky Kalogeiton who is joining our group as new Assistant Professor at Ecole Polytechnique after conducting her Post doc at VGG, Oxford, and her PhD from Univ. Edinburgh and Inria Grenoble. Vicky brings new expertise in deep learning applied to spatial and temporal localization of objects and phenomenon in videos.

Jiayi Wei will start her PhD in our group at fall on “New Geometric representations for Volumetric Brain Analysis”.

June 2020

We are glad to welcome two new international PhD students working on the Innovative Training Network CLIPE aiming at “creating lively interactive populated environments” who will join us in fall: Eduardo Alvarado and Ariel Kwiatkowski.

April 2020

Adrien Poulenard succesfully defended his PhD entitled “Structures for Deep Learning and Topology Optimization for Functions on 3D Shapes”.

March 2020

Marie-Paule Cani become the President of the Computer Science Department (DIX - Departement d’Informatique de l’Ecole Polytechnique).

Thibault Lescoat succesfully defended his PhD entitled “Geometric operators for 3D modeling using dictionary-based shape representations”.

February 2020

Marie-Paule Cani is elected as the President of the SIF (Société Informatique de France) scientific steering committee.

Welcome to our 3 new postdocs: Chrisotphe Lino, Gautam Pai, and Liu Zhisong.

January 2020

  • The project AIGRETTE: Analyzing Large Scale Geometric Data Collections, proposed by Maks Ovsjanikov has been selected as one of the Chaire IA from ANR.
    • In the research project associated with this chair, we propose to develop efficient algorithms and mathematical tools for analyzing large geometric data collections, including 3D shapes represented as triangle or quad meshes, volumetric data, point clouds possibly embedded in high-dimensions and graphs representing geometric (e.g. proximity) data.

November 2019

October 2019

July 2019

March 2019

July 2018