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<!DOCTYPE HTML>
<html lang="en">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Valentin Gabeur</title>
<meta name="author" content="Valentin Gabeur">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon" type="image/png" href="images/valentin_profile_pic.jpg">
</head>
<body>
<table style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
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<td style="padding:2.5%;width:65%;vertical-align:middle">
<p style="text-align:center">
<name>Valentin Gabeur</name>
</p>
<p>
AI researcher at Google DeepMind (Gemini), specializing in multi-modal learning. Postdoc at Meta AI (SAM 2), PhD from Inria, MSc from Toulouse University, MSc from Icam. Former mechanical engineer with 6 years of experience in industrial automation.
</p>
<p>
</p>
<p style="text-align:center">
<a href="mailto:firstname.lastname@gmail.com">Email</a>  / 
<a href="Valentin_Gabeur_CV.pdf">CV</a>  / 
<a href="https://scholar.google.com/citations?user=74zyaaYAAAAJ">Google Scholar</a>  / 
<a href="https://www.linkedin.com/in/gabeur/"> LinkedIn </a>  / 
<a href="https://twitter.com/vgabeur">Twitter</a>  / 
<a href="https://github.com/gabeur"> GitHub </a>
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<a href="images/valentin_profile_pic.jpg"><img style="width:100%;max-width:100%" alt="profile photo" src="images/valentin_profile_pic.jpg" class="hoverZoomLink"></a>
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<td style="padding:20px;width:25%;vertical-align:middle">
<heading>Research publications:</heading>
</td>
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</tbody>
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<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/coq.png" alt="sam2" width="160" height=auto>
</td>
<td width="75%" valign="middle">
<p>
<a href="https://ai.meta.com/blog/segment-anything-2">
<papertitle>SAM 2: Segment Anything in Images and Videos</papertitle>
</a>
<br>
Nikhila Ravi*, <b>Valentin Gabeur*</b>, Yuan-Ting Hu*, Ronghang Hu*, Chaitanya Ryali*, Tengyu Ma*, Haitham Khedr*, Roman Rädle*, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan, Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollár, Christoph Feichtenhofer*
<br>
<em>arXiv, 2024</em>  
<br>
<a href="https://ai.meta.com/research/publications/sam-2-segment-anything-in-images-and-videos/">paper</a> / <a href="https://sam2.metademolab.com/">demo</a> / <a href="https://ai.meta.com/sam2">project page</a> / <a href="https://ai.meta.com/blog/segment-anything-2">blog</a> / <a href="https://ai.meta.com/datasets/segment-anything-video">dataset</a> / <a href=https://github.com/facebookresearch/segment-anything-2>github</a>
<br>
Promptable visual segmentation in images and videos.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/avatar.png" alt="avatar" width="160" height=auto>
</td>
<td width="75%" valign="middle">
<p>
<a href="https://arxiv.org/abs/2206.07684">
<papertitle>AVATAR: Unconstrained Audiovisual Speech Recognition</papertitle>
</a>
<br>
<b>Valentin Gabeur*</b>, Paul Hongsuck Seo*, Arsha Nagrani*, Chen Sun, Karteek Alahari, Cordelia Schmid
<br>
<em>INTERSPEECH, 2022</em>  
<br>
<a href="https://arxiv.org/abs/2206.07684">arXiv</a> / <a href="https://gabeur.github.io/avatar-visspeech">project page</a> / <a href="bib/Gabeur2022Avatar.txt">bibtex</a>
<br>
Leveraging the full frame visual context to improve speech recognition in videos.
</p>
</td>
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<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/MMCVR.png" alt="mmcvr" width="160" height=auto>
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<td width="75%" valign="middle">
<p>
<a href="https://arxiv.org/abs/2111.01300">
<papertitle>Masking Modalities for Cross-modal Video Retrieval</papertitle>
</a>
<br>
<b>Valentin Gabeur</b>, Arsha Nagrani, Chen Sun, Karteek Alahari, Cordelia Schmid
<br>
<em>WACV, 2022</em>  
<br>
<a href="https://arxiv.org/abs/2111.01300">arXiv</a> / <a href="bib/Gabeur2022Masking.txt">bibtex</a>
<br>
Pre-training strategy for learning multi-modal fusion from unlabelled videos.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/MMT.png" alt="mmt" width="160" height=auto>
</td>
<td width="75%" valign="middle">
<p>
<a href="https://arxiv.org/abs/2007.10639">
<papertitle>Multi-modal Transformer for Video Retrieval</papertitle>
</a>
<br>
<b>Valentin Gabeur</b>, Chen Sun, Karteek Alahari, Cordelia Schmid
<br>
<em>ECCV, 2020</em> <b>(Spotlight paper)</b>  
<br>
<a href="https://arxiv.org/abs/2007.10639">arXiv</a> / <a href="https://github.com/gabeur/mmt">code, models, data</a> / <a href="bib/Gabeur2020MMT.txt">bibtex</a>
<br>
Cross-modal architecture to encode language captions and videos in a common embedding space.
</p>
</td>
</tr>
<tr>
<th style="padding:20px;width:25%;vertical-align:middle";text-align: center>
<img src="images/video-pent-logo.svg" alt="video-pent" width="120" height=auto class="center">
</th>
<td width="75%" valign="middle">
<p>
<a href="https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon/technical-reports/MMT.pdf">
<papertitle>CVPR 2020 Video Pentathlon Challenge: Multi-modal Transformer for Video Retrieval</papertitle>
</a>
<br>
<b>Valentin Gabeur</b>, Chen Sun, Karteek Alahari, Cordelia Schmid
<br>
<em>CVPR Video Pentathlon Workshop, 2020</em> <b> (First place)</b>  
<br>
<a href="https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon/technical-reports/MMT.pdf">report</a> /
<a href="https://arxiv.org/pdf/2008.00744.pdf">paper</a> /
<a href="https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon/challenge.html">challenge</a> /
<a href="https://www.youtube.com/watch?v=L2rff2mu1gE">recording</a>
<br>
Winning approach for the <a href="https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon/challenge.html">CVPR 2020 Video Pentathlon Challenge</a>, a video retrieval competition.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/Moulding.png" alt="moulding" width="160" height=auto>
</td>
<td width="75%" valign="middle">
<p>
<a href="https://arxiv.org/abs/1908.00439">
<papertitle>Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images</papertitle>
</a>
<br>
<b>Valentin Gabeur</b>, Jean-Sebastien Franco, Xavier Martin, Cordelia Schmid, Gregory Rogez
<br>
<em>ICCV, 2019</em>  
<br>
<a href="https://arxiv.org/abs/1908.00439">arXiv</a> / <a href="bib/Gabeur2019Moulding.txt">bibtex</a>
<br>
Efficient 3D shape representation through the combination of depth maps.
</p>
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<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
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<td style="padding:0px">
<br>
<p style="text-align:right;font-size:small;">
Credits to <a href="https://jonbarron.info/">Jon Barron</a> for the template.
</p>
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