# Comixify: Transform video into a comics

## TL;DR

This paper introduces Comixify, a neural network-based system that converts videos into comic-style images through keyframe extraction and style transfer, resulting in a web application for video comixification.

## Contribution

It presents a novel end-to-end solution combining keyframe extraction and style transfer using GANs, creating a practical web app for video to comic transformation.

## Key findings

- Effective keyframe extraction algorithm developed
- State-of-the-art style transfer applied to video frames
- Functional web application for video comixification

## Abstract

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