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15 lines
1.3 KiB
Markdown
15 lines
1.3 KiB
Markdown
Repository with code for the "Comixify: Transform video into a comics" paper, that can be found here:
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https://arxiv.org/abs/1812.03473
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In this paper, we propose a solution to transform a video into a comics. We approach this task using a
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neural style algorithm based on Generative Adversarial Networks (GANs). Several recent works in
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the field of Neural Style Transfer showed that producing an image in the style of another image is
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feasible. In this paper, we build up on these works and extend the existing set of style transfer use
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cases with a working application of video comixification. To that end, we train an end-to-end solution
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that transforms input video into a comics in two stages. In the first stage, we propose a state-of-the-art
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keyframes extraction algorithm that selects a subset of frames from the video to provide the most
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comprehensive video context and we filter those frames using image aesthetic estimation engine. In
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the second stage, the style of selected keyframes is transferred into a comics. To provide the most
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aesthetically compelling results, we selected the most state-of-the art style transfer solution and based
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on that implement our own ComixGAN framework. The final contribution of our work is a Web-based
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working application of video comixification available at http://comixify.ii.pw.edu.pl
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