<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
	<channel>
		<title>Jean-Marie Morvan on Imagine Team</title>
		<link>https://projet.liris.cnrs.fr/imagine/authors/jean-marie-morvan/</link>
		<description>Recent content in Jean-Marie Morvan on Imagine Team</description>
		<generator>Hugo</generator>
		<language>en-US</language>
		
		
		
			<copyright>&amp;copy; 2026 IMAGINE team - LIRIS</copyright>
		
		
			<lastBuildDate>Mon, 01 Jan 2018 00:00:00 +0000</lastBuildDate>
		
			<atom:link href="https://projet.liris.cnrs.fr/imagine/authors/jean-marie-morvan/index.xml" rel="self" type="application/rss+xml" />
			<item>
				<title>Improving Shadow Suppression for Illumination Robust Face Recognition</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01704659/</link>
				<pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01704659/</guid>
				<description></description>
			</item>
			<item>
				<title>An efficient multimodal 2D &#43; 3D feature-based approach to automatic facial expression recognition</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-02130337/</link>
				<pubDate>Thu, 01 Jan 2015 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-02130337/</guid>
				<description></description>
			</item>
			<item>
				<title>3D assisted face recognition via progressive pose estimation</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01301118/</link>
				<pubDate>Wed, 01 Jan 2014 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01301118/</guid>
				<description></description>
			</item>
			<item>
				<title>Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01271744/</link>
				<pubDate>Wed, 01 Jan 2014 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01271744/</guid>
				<description></description>
			</item>
			<item>
				<title>Towards 3D Face Recognition in the Real: A Registration-Free Approach using Fine-Grained Matching of 3D Keypoint Descriptors</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01301114/</link>
				<pubDate>Wed, 01 Jan 2014 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01301114/</guid>
				<description></description>
			</item>
			<item>
				<title>Surface Meshing with Curvature Convergence</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01351708/</link>
				<pubDate>Tue, 01 Jan 2013 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01351708/</guid>
				<description></description>
			</item>
			<item>
				<title>3D Facial Expression Recognition Based on Histograms of Surface Differential Quantities</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01354564/</link>
				<pubDate>Sat, 01 Jan 2011 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01354564/</guid>
				<description></description>
			</item>
			<item>
				<title>Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01354563/</link>
				<pubDate>Sat, 01 Jan 2011 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01354563/</guid>
				<description></description>
			</item>
			<item>
				<title>Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition</title>
				<link>https://projet.liris.cnrs.fr/imagine/publications/hal-01354565/</link>
				<pubDate>Sat, 01 Jan 2011 00:00:00 +0000</pubDate>
				<guid>https://projet.liris.cnrs.fr/imagine/publications/hal-01354565/</guid>
				<description></description>
			</item>
	</channel>
</rss>
