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<!DOCTYPE HTML>
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<title>Sarah Ibrahimi | PhD Candidate - University of Amsterdam</title>
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<h2>Sarah Ibrahimi</h2>
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<p>PhD candidate</p>
<p>University of Amsterdam</p>
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<p>I am a PhD candidate in Computer Vision at the University of Amsterdam, supervised by Marcel Worring. My main areas of interests are Multimodal Learning, Visual Retrieval tasks, AI & Creativity and more recently Hyperbolic Learning.</p>
<p>My background is in Computer Science with a specialization in Cyber Security (MSc 2014, Eindhoven University of Technology) and Mathematics (BSc 2012, Utrecht University). Besides, I have a background in Theater and Dance Studies (BA 2012, Utrecht University).</p>
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<h3 style="text-align: center">News</h3>
<ul>
<li>08/2023: I started as an Applied Scientist Intern in the New Initiatives team of Amazon Just Walk Out, where I'm working with Greg Hager and Austin Reiter. During this internship, I will work on uncertainty quantification on vision-language models.</li>
<li>07/2023: Our work <a href="https://arxiv.org/pdf/2307.12964.pdf">Audio-Enhanced Text-to-Video Retrieval using Text-Conditioned Feature Alignment</a> has been accepted as an oral at ICCV 2023. This work is the result of my internship at <a href="https://www.amazon.science">Amazon Prime Video</a>.</li>
<li>08/2022: I started as an Applied Scientist Intern in the Multimodal Video Understanding team of Amazon Prime Video, led by Mohamed Omar. During this internship, I will work on audio-enhanced text-video retrieval.</li>
<li>10/2021: Our work <a href="https://drive.google.com/file/d/1Ix7KsQtRa2qYFG-N9N8bx5DcbX_PFfk4/view?usp=sharing">Learning with Label Noise for Image Retrieval by Selecting Interactions</a> has been accepted at WACV 2022. This work is the result of my internship at <a href="https://europe.naverlabs.com">Naver Labs Europe</a>.</li>
<li>10/2021: Our work <a href="https://drive.google.com/file/d/1OFKI9jbtCcV9AD3bKsnJshPDf6ehtQji/view?usp=sharing">Inside Out Visual Place Recognition</a> has been accepted at BMVC 2021. In this work we present the new task Inside Out Visual Place Recognition where the goal is to localize indoor images together with a new dataset.</li>
<li>10/2021: Our work <a href="https://openreview.net/pdf?id=fnuAjFL7MXy">Instance-level Recognition for Artworks: The Met Dataset</a> has been accepted at NeurIPS 2021, Datasets and Benchmark Track.</a></li>
<li>09/2021: My work <a href="https://computationalcreativity.net/iccc21/wp-content/uploads/2021/09/ICCC_2021_paper_114.pdf">Composition, Performance and Evaluation: A Dance Education Framework for AI Systems</a> has been accepted at the International Conference on Computational Creativity 2021.</a></li>
<li>07/2021: I finished my internship at <a href="https://europe.naverlabs.com">Naver Labs Europe</a> which resulted in two papers that are currently under submission.</a></li>
<li>06/2021: My work 'A Comparison between Dance Generation Algorithms and Choreographers' has been accepted at the CVPR Workshop on Ethical Considerations in Creative applications of Computer Vision 2021.</a></li>
<li>01/2021: I started as a Research Intern at <a href="https://europe.naverlabs.com">Naver Labs Europe</a> in the Machine Learning and Optimization team where I'll be working on optimizing interaction losses and learning with noisy labels.</a></li>
<li>05/2020: Our work on <a href="https://openaccess.thecvf.com/content_CVPRW_2020/papers/w39/Hulzebosch_Detecting_CNN-Generated_Facial_Images_in_Real-World_Scenarios_CVPRW_2020_paper.pdf">Detecting CNN-Generated Facial Images in Real-World Scenarios</a> has been accepted at the CVPR Workshop on Media Forensics 2020.</a></li>
<li>05/2020: Our work <a href="https://arxiv.org/pdf/2005.04909">Conditional Image Generation and Manipulation for User-Specified Content</a> has been accepted at the CVPR AI for Content Creation Workshop 2020.</a></li>
<li>10/2019: I presented our work on <a href="http://openaccess.thecvf.com/content_ICCVW_2019/papers/CVFAD/Ibrahimi_Deep_Metric_Learning_for_Cross-Domain_Fashion_Instance_Retrieval_ICCVW_2019_paper.pdf">Deep Metric Learning for Cross-Domain Fashion Instance Retrieval </a> at the <a href="https://sites.google.com/view/cvcreative">ICCV Workshop on Computer Vision for Fashion, Art and Design</a>.</li>
<li>07/2019: Our work on <a href="https://dl.acm.org/citation.cfm?id=3350597">Multimodal Semantic Matching</a> has been accepted at ACM Multimedia 2019 as a demo paper.</a></li>
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<h2 style="text-align: center"><a id="two">Publications</a></h2>
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<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/iccv2023.png" width="180" alt="" style="border:none;" /></div>
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<header>
<h4>Audio-Enhanced Text-to-Video Retrieval using Text-Conditioned Feature Alignment</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Xiaohang Sun, Pichao Wang, Amanmeet Garg, Ashutosh Sanan, Mohamed Omar <span style="font-weight: bold">Audio-Enhanced Text-to-Video Retrieval using Text-Conditioned Feature Alignment</span>, (ICCV 2023, oral) [<a
href="https://arxiv.org/pdf/2307.12964.pdf">Link</a>].</p>
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<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/wacv.pdf" width="180" alt="" style="border:none;" /></div>
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<div class="9u$ 8u$(large) 12u$(medium)">
<header>
<h4>Learning with Label Noise for Image Retrieval by Selecting Interactions</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Arnaud Sors, Rafael Sampaio de Rezende, Stéphane Clinchant <span style="font-weight: bold">Learning with Label Noise for Image Retrieval by Selecting Interactions</span>, (WACV 2022) [<a
href="https://drive.google.com/file/d/1Ix7KsQtRa2qYFG-N9N8bx5DcbX_PFfk4/view?usp=sharing">Link</a>].</p>
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<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/iovpr.png" width="180" alt="" style="border:none;" /></div>
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<header>
<h4>Inside Out Visual Place Recognition</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Nanne van Noord, Tim Alpherts, Marcel Worring <span style="font-weight: bold">Inside Out Visual Place Recognition</span>, (BMVC 2021) [<a
href="https://drive.google.com/file/d/1OFKI9jbtCcV9AD3bKsnJshPDf6ehtQji/view?usp=sharing">Link</a>].</p>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/fig_dataset_met_revisited_queries.pdf" width="180" alt="" style="border:none;" /></div>
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<div class="9u$ 8u$(large) 12u$(medium)">
<header>
<h4>Instance-level Recognition for Artworks: The MET Dataset</h4>
</header>
<p>Nikolaos-Antonios Ypsilantis, Noa Garcia, Guangxing Han, <span style="text-decoration: underline;">Sarah Ibrahimi</span>, Nanne van Noord, Giorgos Tolias, <span style="font-weight: bold"> Instance-level Recognition for Artworks: The Met Dataset</span>, (NeurIPS 2021, Datasets and Benchmarks Track) [<a
href="https://openreview.net/pdf?id=fnuAjFL7MXy">Link</a>].</p>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image rounded"><img src="images/no_image.png" width="180" alt="" style="border:none;" /></div>
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<div class="9u$ 8u$(large) 12u$(medium)">
<header>
<h4>Composition, Performance and Evaluation: A Dance Education Framework for AI Systems</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span> <span style="font-weight: bold">Composition, Performance and Evaluation: A Dance Education Framework for AI Systems</span>, (ICCC 2021) [<a
href="https://computationalcreativity.net/iccc21/wp-content/uploads/2021/09/ICCC_2021_paper_114.pdf">Link</a>].</p>
</div>
</div>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/detecting.png" width="180" alt="" style="border:none;" /></div>
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<div class="9u$ 8u$(large) 12u$(medium)">
<header>
<h4>Detecting CNN-Generated Facial Images in Real-World Scenarios</h4>
</header>
<p>Nils Hulzebosch, <span style="text-decoration: underline;">Sarah Ibrahimi</span>, Marcel Worring, <span style="font-weight: bold">Detecting CNN-Generated Facial Images in Real-World Scenarios</span>, (CVPRW 2020) [<a
href="https://openaccess.thecvf.com/content_CVPRW_2020/papers/w39/Hulzebosch_Detecting_CNN-Generated_Facial_Images_in_Real-World_Scenarios_CVPRW_2020_paper.pdf">PDF</a>].</p>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/ai4cc.png" width="180" alt="" style="border:none;" /></div>
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<header>
<h4>Conditional Image Generation and Manipulation for User-Specified Content</h4>
</header>
<p>David Stap, Maurits Bleeker, <span style="text-decoration: underline;">Sarah Ibrahimi</span>, Maartje ter Hoeve, <span style="font-weight: bold">Conditional Image Generation and Manipulation for User-Specified Content</span>, (CVPRW 2020) [<a
href="https://arxiv.org/pdf/2005.04909.pdf">PDF</a>].</p>
</div>
</div>
<hr />
<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image rounded"><img src="images/fashion.png" width="180" alt="" style="border:none;" /></div>
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<div class="9u$ 8u$(large) 12u$(medium)">
<header>
<h4>Deep Metric Learning for Cross-Domain Fashion Instance Retrieval</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Nanne van Noord, Zeno Geradts, Marcel Worring, <span style="font-weight: bold">Deep Metric Learning for Cross-Domain Fashion Instance Retrieval</span>, (ICCVW 2019) [<a
href="http://openaccess.thecvf.com/content_ICCVW_2019/papers/CVFAD/Ibrahimi_Deep_Metric_Learning_for_Cross-Domain_Fashion_Instance_Retrieval_ICCVW_2019_paper.pdf">PDF</a>].</p>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image fit"><img src="images/mm.png" width="180" alt="" style="border:none;" /></div>
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<header>
<h4>Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Shuo Chen, Devanshu Arya, Arthur Câmara, Yunlu Chen, Tanja Crijns, Maurits van der Goes, Thomas Mensink, Emiel van Miltenburg, Daan Odijk, William Thong, Jiaojiao Zhao, Pascal Mettes. <span style="font-weight: bold">Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching</span>, (ACM Multimedia 2019) [<a
href="https://dl.acm.org/citation.cfm?id=3350597">Link</a>].</p>
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<div class="row 200%">
<div class="3u 4u(large) 12u$(medium)">
<div class="image rounded"><img src="images/no_image.png" width="180" alt="" style="border:none;" /></div>
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<header>
<h4>Riding the saddle point: asymptotics of the capacity-achieving simple decoder for bias-based traitor tracing</h4>
</header>
<p><span style="text-decoration: underline;">Sarah Ibrahimi</span>, Boris Škorić, Jan-Jaap Oosterwijk, <span style="font-weight: bold">Riding the saddle point: asymptotics of the capacity-achieving simple decoder for bias-based traitor tracing</span>, EURASIP Journal on Information Security 2014, 2014:12 [<a
href="https://link.springer.com/article/10.1186/s13635-014-0012-6">Link</a>].</p>
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<p><span style="font-weight: bold">S [DOT] IBRAHIMI [AT] UVA [DOT] NL</span><br /> Intelligent Sensory Information Systems, University of Amsterdam<br />Science Park 904, 1098 XH Amsterdam, The Netherlands</p>
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