Maks Ovsjanikov

I am a professor in the Computer Science department at Ecole Polytechnique in France. I am a member of the GeoViC group at the LIX research laboratory of Ecole Polytechnique and an associate member (external collaborator) of the DataShape team at INRIA. My current research is mainly supported by my ERC Starting Grant: EXPROTEA.

My research is primarily related to geometric (3D) shape analysis with emphasis on Deep Learning for non-rigid shape comparison and processing. In the past, I have worked on topics including shape classification and retrieval, non-rigid shape-matching, comparison, denoising and symmetry detection especially on 3D point cloud and triangle mesh data. I'm also very interested in image processing, Computer Graphics and Computer Vision in general. You can find some of my work on the Publications page.

Recent News

June 2021

    Adrien Poulenard, who did a PhD in our group, has won the best thesis award from the IDIA department of IP Paris. He gave a short 10 minute talk on this occasion, to summarize some of this work, which can be found here. Congratulations to him!

    Our paper on Discrete Optimization of Shape Matching has been accepted at the Symposium on Geometry Processing (SGP) 2021.

April 2021

March 2021

    I'm very happy to be part of 4 papers accepted at CVPR 2021:

    • ArtEmis: Affective Language for Visual Art with Panos Achlioptas, Kilichbek Haydarov, Mohamed Elhoseiny and Leonidas Guibas (oral)
    • Physically-aware Generative Network for 3D Shape Modeling with Mariem Mezghanni, Malika Boulkenafed and Andre Lieutier (poster)
    • Learning Delaunay Surface Elements for Mesh Reconstruction with Paul Guerrero, Noam Aigerman and Niloy Mitra (oral)
    • Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence with Functional Maps with Gautam Pai, Jing Ren, Peter Wonka and Simone Melzi (poster)
    The pre-prints are now on my Publications page.

    I gave a talk in the TUM AI Lecture Series. The talk was on various ways of modeling and solving matching problems with learning techniques.

February 2021

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