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Dmitrii Tarasov
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@@ -147,16 +147,12 @@ <h2 class="title is-3">Abstract</h2>
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<h2 class="title is-3 has-text-centered">Reconstruct images from feature space</h2>
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<div class="content">
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<div class="has-text-centered">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/features_reconstruction.drawio.png" alt="features_reconstruction" class="is-rounded">
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</figure>
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<img src="./static/images/features_reconstruction.drawio.png" alt="features_reconstruction" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 1. Image reconstructor training.</b> For pretrained model we train a reconstructor model that
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restores the image from the feature space.
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</p>
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/reconstruction_metrics.jpg" alt="reconstruction_metrics" class="is-rounded">
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</figure>
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<img src="./static/images/reconstruction_metrics.jpg" alt="reconstruction_metrics" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 2. Reconstruction Metrics.</b> We show the results of the reconstruction for SigLip and SigLip2
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for different image resultions.
@@ -185,17 +181,13 @@ <h2 class="title is-3 has-text-centered">Feature-space transformations. Q matrix
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<div class="content">
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<div class="columns is-centered">
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/features_reconstruction_manipulation_train_Q.drawio.png" alt="features_reconstruction_manipulation_train_Q" class="is-rounded">
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</figure>
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<img src="./static/images/features_reconstruction_manipulation_train_Q.drawio.png" alt="features_reconstruction_manipulation_train_Q" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 3. Feature-space transformations. Q matrix Calculation.</b> We then calculate Q matrix for feature-space manupulation.
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</p>
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</div>
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/features_reconstruction_manipulation_eval_Q.drawio.png" alt="features_reconstruction_manipulation_eval_Q" class="is-rounded">
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</figure>
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<img src="./static/images/features_reconstruction_manipulation_eval_Q.drawio.png" alt="features_reconstruction_manipulation_eval_Q" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 4. Feature-space transformations. Q matrix Application.</b> After Q matrix is calculated, we apply it to the feature space. For each patch embedding.
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</p>
@@ -215,17 +207,13 @@ <h2 class="title is-3 has-text-centered">Feature-space transformations. Color Sw
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<div class="content">
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<div class="columns is-centered">
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/rb_swap.png" alt="rb_swap" class="is-rounded">
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</figure>
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<img src="./static/images/rb_swap.png" alt="rb_swap" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 5. Red-blue channel swap samples.</b>
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</p>
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</div>
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/color_swap_all_eigen_values.png" alt="color_swap_all_eigen_values" class="is-rounded">
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</figure>
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<img src="./static/images/color_swap_all_eigen_values.png" alt="color_swap_all_eigen_values" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 6. 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>
@@ -245,17 +233,13 @@ <h2 class="title is-3 has-text-centered">Feature-space transformations. Blue Cha
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<div class="content">
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<div class="columns is-centered">
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/b_suppression_all_transformations.png" alt="b_suppression_all_transformations" class="is-rounded">
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</figure>
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<img src="./static/images/b_suppression_all_transformations.png" alt="b_suppression_all_transformations" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 7. Blue channel suppression samples.</b>
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</p>
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</div>
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<div class="column is-half">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/b_suppression_all_eigen_values.png" alt="b_suppression_all_eigen_values" class="is-rounded">
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</figure>
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<img src="./static/images/b_suppression_all_eigen_values.png" alt="b_suppression_all_eigen_values" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 8. Eigenvalues for blue channel suppression matrix.</b>
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</p>
@@ -274,9 +258,7 @@ <h2 class="title is-3 has-text-centered">Feature-space transformations. Blue Cha
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<h2 class="title is-3 has-text-centered">Feature-space transformations. Colorization.</h2>
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<div class="content">
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<div class="has-text-centered">
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<figure class="image is-16by9 mb-6">
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<img src="./static/images/colorized_examples.png" alt="colorization_all_transformations" class="is-rounded">
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</figure>
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<img src="./static/images/colorized_examples.png" alt="colorization_all_transformations" class="is-rounded">
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<p class="caption has-text-centered mb-6">
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<b>Figure 9. Colorization samples.</b>
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</p>

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