Large-scale shape retrieval with sparse 3D convolutional neural networks

Alexandr Notchenko, Yermek Kapushev, Evgeny Burnaev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    14 Citations (Scopus)

    Abstract

    In this paper we present results of performance evaluation of S3DCNN — a Sparse 3D Convolutional Neural Network — on a large-scale 3D Shape benchmark ModelNet40, and measure how it is impacted by voxel resolution of input shape. We demonstrate comparable classification and retrieval performance to state-of-the-art models, but with much less computational costs in training and inference phases. We also notice that benefits of higher input resolution can be limited by an ability of a neural network to generalize high level features.

    Original languageEnglish
    Title of host publicationAnalysis of Images, Social Networks and Texts - 6th International Conference, AIST 2017, Revised Selected Papers
    EditorsAndrey V. Savchenko, Dmitry I. Ignatov, Sergei O. Kuznetsov, Irina A. Lomazova, Victor Lempitsky, Michael Khachay, Natalia Loukachevitch, Amedeo Napoli, Wil M. van der Aalst, Alexander Panchenko, Panos M. Pardalos, Stanley Wasserman
    PublisherSpringer Verlag
    Pages245-254
    Number of pages10
    ISBN (Print)9783319730127
    DOIs
    Publication statusPublished - 2018
    Event6th International Conference on Analysis of Images, Social Networks and Texts, AIST 2017 - Moscow, Russian Federation
    Duration: 27 Jul 201729 Jul 2017

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10716 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference6th International Conference on Analysis of Images, Social Networks and Texts, AIST 2017
    Country/TerritoryRussian Federation
    CityMoscow
    Period27/07/1729/07/17

    Keywords

    • Deep learning
    • Sparse 3D convolutional neural network
    • Voxel resolution

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