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‎project/index.html‎

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<title>Image Reconstruction as a Tool for Feature Analysis</title>
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<link rel="icon" type="image/x-icon" href="static/images/favicon.ico">
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<link rel="icon" type="image/x-icon" href="static/images/favicon.png">
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<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel="stylesheet">
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<div class="column has-text-centered">
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<h1 class="title is-1 publication-title">Image Reconstruction as a Tool for Feature Analysis</h1>
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<div class="is-size-5 publication-authors">
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<!-- Paper authors -->
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<span class="author-block">
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<a href="mailto:allakhverdov@2a2i.org" target="_blank">Eduard Allakhverdov</a>
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<strong>Eduard Allakhverdov</strong><sup>§†</sup>,&nbsp;
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</span>
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<span class="author-block">
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<a href="mailto:d.tarasov@airi.net" target="_blank">Dmitrii Tarasov</a>
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<strong>Dmitrii Tarasov</strong><sup>§</sup>,&nbsp;
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<span class="author-block">
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<a href="mailto:goncharova@airi.net" target="_blank">Elizaveta Goncharova</a>
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<strong>Elizaveta Goncharova</strong><sup>§</sup>,&nbsp;
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<span class="author-block">
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<a href="mailto:kuznetsov@airi.net" target="_blank">Andrey Kuznetsov</a>
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</span>
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</div>
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<div class="is-size-5 publication-authors">
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<span class="author-block">
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AIRI, Moscow, Russia<br>
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MIPT, Dolgoprudny, Russia
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</span>
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<span class="author-block">
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AIRI, Moscow, Russia
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</span>
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AIRI, Moscow, Russia
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</span>
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<span class="author-block">
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AIRI, Moscow, Russia
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<strong>Andrey Kuznetsov</strong><sup>§</sup>,&nbsp;
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<ul>
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<sup>§</sup> AIRI, <sup>†</sup> MIPT
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</ul>
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<!-- ArXiv abstract Link -->
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<!-- TODO: add arXiv link -->
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<a href="https://arxiv.org/abs/<ARXIV PAPER ID>" target="_blank"
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<!-- Базовые результаты: siglip vs siglip2 -->
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<!-- Нужно четко подчеркнуть какие различия между модельками -->
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<!-- И как это влияет на реконструкцию -->
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<!-- -->
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<div class="columns is-centered has-text-centered">
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<div class="column is-four-fifths">
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<h2 class="title is-3" style="white-space: nowrap;">Reconstruct images from feature space</h2>
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<div class="content has-text-justified">
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<div style="text-align: center;">
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<img src="./static/images/features_reconstruction.drawio.png" alt="features_reconstruction" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 1. Image reconstructor training.</b> For pretrained model we train a reconstructor model that restores the image from the feature space.
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</p>
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<img src="./static/images/reconstruction_metrics.jpg" alt="reconstruction_metrics" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 2. Reconstruction Metrics.</b> We show the results of the reconstruction for SigLip and SigLip2 for different image resultions.
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</p>
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</div>
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</div>
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<br><br>
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</div>
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</div>
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<!-- (2) Feature-space transformations -->
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<!-- Текстовое объяснение -->
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<!-- Визуализация фреймворка: обобщил оператор в пр-ве картинок и в пр-ве фичей -->
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<!-- Сделать видос с визуализацией фреймворка -->
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<!-- Примеры работы с RGB -->
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<!-- Примеры работы с отключением одного канала (ожелтением) -->
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<!-- Примеры Спектра такой м-цы, показать, что только небольшое кол-во каналов меняется -->
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<!-- -->
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<!-- Image carousel -->
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<section class="hero is-small">
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<div class="hero-body">
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<div class="container">
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<div id="results-carousel" class="carousel results-carousel">
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<div class="item">
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<!-- Your image here -->
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<img src="static/images/v1_vs_v2.png" alt="Comparison of SigLIP and SigLIP2 reconstructions" />
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<h2 class="subtitle has-text-centered">
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Comparison of image reconstructions from SigLIP and SigLIP2 feature spaces.
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</h2>
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<div class="columns is-centered has-text-centered">
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<div class="column is-four-fifths">
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations</h2>
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<div class="content has-text-justified">
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<div style="text-align: center;">
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<img src="./static/images/features_reconstruction_manipulation.drawio.png" alt="features_reconstruction_manipulation" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 3. Feature-space transformations.</b> We then calculate Q matrix for feature-space manupulation.
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</p>
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<img src="./static/images/rb_swap.png" alt="rb_swap" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 4. Red-blue channel swap samples.</b> We then calculate Q matrix for feature-space manupulation.
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</p>
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<img src="./static/images/rb_swap_eigenvalues.png" alt="rb_swap_eigenvalues" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 5. Eigenvalues for red-blue channel swap matrix.</b> Majority of eigenvalues are close to 1, which means that the transformation is close to an identity matrix. While the other cluster of eigenvalues are close to -1, which means that for these channels direction is changed to the opposite.
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</p>
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</div>
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<div class="item">
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<!-- Your image here -->
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<img src="static/images/rb_swap.png" alt="Red-Blue channel swap visualization" />
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<h2 class="subtitle has-text-centered">
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Visualization of feature space manipulation through red-blue channel swap.
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</h2>
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<br><br>
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</div>
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</div>
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</section>
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<!-- TODO: add citation -->
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<!--BibTex citation -->
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<section class="section" id="BibTeX">
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<div class="container is-max-desktop content">

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‎project/static/images/features_reconstruction.drawio.png‎

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‎project/static/images/features_reconstruction_manipulation.drawio.png‎

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‎project/static/images/rb_swap_eigenvalues.png‎

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‎project/static/images/reconstruction_metrics.jpg‎

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