<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-04820475</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-20T02:51:37+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Improving Neural Network Surface Processing with Principal Curvatures</title>
            <author role="aut">
              <persName>
                <forename type="first">Josquin</forename>
                <surname>Harrison</surname>
              </persName>
              <email type="md5">13754f23824b58be69746b8dd84778ad</email>
              <email type="domain">inria.fr</email>
              <idno type="idhal" notation="numeric">1471293</idno>
              <idno type="halauthorid" notation="string">2308264-1471293</idno>
              <affiliation ref="#struct-525212"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">James</forename>
                <surname>Benn</surname>
              </persName>
              <email type="md5">b1f8c6cf7e4755f19c98c6255214760d</email>
              <email type="domain">inria.fr</email>
              <idno type="idhal" notation="numeric">1125250</idno>
              <idno type="halauthorid" notation="string">2420187-1125250</idno>
              <affiliation ref="#struct-525212"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Maxime</forename>
                <surname>Sermesant</surname>
              </persName>
              <email type="md5">ab1461a79f36047bdd95798e18f750bf</email>
              <email type="domain">inria.fr</email>
              <idno type="idhal" notation="string">maxime-sermesant</idno>
              <idno type="idhal" notation="numeric">2423</idno>
              <idno type="halauthorid" notation="string">945-2423</idno>
              <idno type="ORCID">https://orcid.org/0000-0002-6256-8350</idno>
              <idno type="GOOGLE SCHOLAR">https://scholar.google.com/citations?user=LTDUiAkAAAAJ</idno>
              <idno type="IDREF">https://www.idref.fr/077430409</idno>
              <affiliation ref="#struct-525212"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Josquin</forename>
                <surname>HARRISON</surname>
              </persName>
              <email type="md5">13754f23824b58be69746b8dd84778ad</email>
              <email type="domain">inria.fr</email>
            </editor>
            <funder ref="#projeurop-713987"/>
            <funder ref="#projeurop-712318"/>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2024-12-05 11:48:10</date>
              <date type="whenModified">2025-08-26 15:21:01</date>
              <date type="whenReleased">2024-12-05 19:27:28</date>
              <date type="whenProduced">2024-12-10</date>
              <date type="whenEndEmbargoed">2024-12-05</date>
              <ref type="file" target="https://hal.science/hal-04820475v1/document">
                <date notBefore="2024-12-05"/>
              </ref>
              <ref type="file" n="1" target="https://hal.science/hal-04820475v1/file/Curvature-12.pdf" id="file-4820475-4199007">
                <date notBefore="2024-12-05"/>
              </ref>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="1574848">
                <persName>
                  <forename>Josquin</forename>
                  <surname>HARRISON</surname>
                </persName>
                <email type="md5">13754f23824b58be69746b8dd84778ad</email>
                <email type="domain">inria.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-04820475</idno>
            <idno type="halUri">https://hal.science/hal-04820475</idno>
            <idno type="halBibtex">harrison:hal-04820475</idno>
            <idno type="halRefHtml">&lt;i&gt;Neurips 2024 - 38th Annual Conference on Neural Information Processing Systems&lt;/i&gt;, Dec 2024, Vancouver, Canada</idno>
            <idno type="halRef">Neurips 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada</idno>
            <availability status="restricted">
              <licence target="https://about.hal.science/hal-authorisation-v1/">HAL Authorization<ref corresp="#file-4820475-4199007"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno>
            <idno type="stamp" n="INRIA-SOPHIA">INRIA Sophia Antipolis - Méditerranée</idno>
            <idno type="stamp" n="INRIASO">INRIA-SOPHIA</idno>
            <idno type="stamp" n="OPENAIRE">OpenAIRE</idno>
            <idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno>
            <idno type="stamp" n="TESTALAIN1">TESTALAIN1</idno>
            <idno type="stamp" n="INRIA2">INRIA 2</idno>
            <idno type="stamp" n="UNIV-COTEDAZUR">Université Côte d'Azur</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="invited" n="0">No</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
            <note type="proceedings" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Improving Neural Network Surface Processing with Principal Curvatures</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Josquin</forename>
                    <surname>Harrison</surname>
                  </persName>
                  <email type="md5">13754f23824b58be69746b8dd84778ad</email>
                  <email type="domain">inria.fr</email>
                  <idno type="idhal" notation="numeric">1471293</idno>
                  <idno type="halauthorid" notation="string">2308264-1471293</idno>
                  <affiliation ref="#struct-525212"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">James</forename>
                    <surname>Benn</surname>
                  </persName>
                  <email type="md5">b1f8c6cf7e4755f19c98c6255214760d</email>
                  <email type="domain">inria.fr</email>
                  <idno type="idhal" notation="numeric">1125250</idno>
                  <idno type="halauthorid" notation="string">2420187-1125250</idno>
                  <affiliation ref="#struct-525212"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Maxime</forename>
                    <surname>Sermesant</surname>
                  </persName>
                  <email type="md5">ab1461a79f36047bdd95798e18f750bf</email>
                  <email type="domain">inria.fr</email>
                  <idno type="idhal" notation="string">maxime-sermesant</idno>
                  <idno type="idhal" notation="numeric">2423</idno>
                  <idno type="halauthorid" notation="string">945-2423</idno>
                  <idno type="ORCID">https://orcid.org/0000-0002-6256-8350</idno>
                  <idno type="GOOGLE SCHOLAR">https://scholar.google.com/citations?user=LTDUiAkAAAAJ</idno>
                  <idno type="IDREF">https://www.idref.fr/077430409</idno>
                  <affiliation ref="#struct-525212"/>
                </author>
              </analytic>
              <monogr>
                <title level="m">NeurIPS Proceedings</title>
                <meeting>
                  <title>Neurips 2024 - 38th Annual Conference on Neural Information Processing Systems</title>
                  <date type="start">2024-12-10</date>
                  <date type="end">2024-12-15</date>
                  <settlement>Vancouver</settlement>
                  <country key="CA">Canada</country>
                </meeting>
                <imprint>
                  <biblScope unit="volume">2024</biblScope>
                </imprint>
              </monogr>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en">Surface processing</term>
                <term xml:lang="en">Deep learning</term>
              </keywords>
              <classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode>
              <classCode scheme="halDomain" n="info.info-cg">Computer Science [cs]/Computational Geometry [cs.CG]</classCode>
              <classCode scheme="halTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halOldTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halTreeTypology" n="COMM">Conference papers</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>The modern study and use of surfaces is a research topic grounded in centuries of mathematical and empirical inquiry. From a mathematical point of view, curvature is an invariant that characterises the intrinsic geometry and the extrinsic shape of a surface. Yet, in modern applications the focus has shifted away from finding expressive representations of surfaces, and towards the design of efficient neural network architectures to process them. The literature suggests a tendency to either overlook the representation of the processed surface, or use overcomplicated representations whose ability to capture the essential features of a surface is opaque. We propose using curvature as the input of neural network architectures for surface processing, and explore this proposition through experiments making use of the shape operator. Our results show that using curvature as input leads to significant a increase in performance on segmentation and classification tasks, while allowing far less computational overhead than current methods.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="researchteam" xml:id="struct-525212" status="VALID">
          <idno type="RNSR">201822641L</idno>
          <idno type="ROR">https://ror.org/05sxdf220</idno>
          <orgName>E-Patient : Images, données &amp; mOdèles pour la médeciNe numériquE</orgName>
          <orgName type="acronym">EPIONE</orgName>
          <date type="start">2018-01-01</date>
          <date type="end">2027-12-31</date>
          <desc>
            <address>
              <addrLine>2004 route des Lucioles BP 93 06902 Sophia Antipolis</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.inria.fr/equipes/epione</ref>
          </desc>
          <listRelation>
            <relation active="#struct-34586" type="direct"/>
            <relation active="#struct-300009" type="indirect"/>
          </listRelation>
        </org>
        <org type="laboratory" xml:id="struct-34586" status="VALID">
          <idno type="RNSR">198318250R</idno>
          <idno type="ROR">https://ror.org/01nzkaw91</idno>
          <orgName>Centre Inria d'Université Côte d'Azur</orgName>
          <desc>
            <address>
              <addrLine>2004 route des Lucioles BP 93 06902 Sophia Antipolis</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inria.fr/centre/sophia/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-300009" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-300009" status="VALID">
          <idno type="ROR">https://ror.org/02kvxyf05</idno>
          <orgName>Institut National de Recherche en Informatique et en Automatique</orgName>
          <orgName type="acronym">Inria</orgName>
          <desc>
            <address>
              <addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inria.fr/en/</ref>
          </desc>
        </org>
      </listOrg>
      <listOrg type="projects">
        <org type="europeanProject" xml:id="projeurop-713987" status="INCOMING">
          <desc>ERACoSysMed PARIS</desc>
        </org>
        <org type="europeanProject" xml:id="projeurop-712318" status="VALID">
          <idno type="number">786854</idno>
          <idno type="program">ERC-2017-ADG</idno>
          <idno type="call">ERC-2017-ADG</idno>
          <orgName>G-Statistics</orgName>
          <desc>Foundations of Geometric Statistics and Their Application in the Life Sciences</desc>
          <date type="start">2018-09-01</date>
          <date type="end">2024-08-31</date>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>