The deepfakes algorithm involves training of deep neural networks called autoencoders. Tl dr version: it can swap the face of anyone in a video with anybody else’s face using Autoencoders and Convolutional Neural Networks. Note: Here is a great explanation of how the deepfakes algorithm works. My focus in this project lies on recreating the player faces from within the game and improving them to make them look exactly like the actual players. It is a Deep Neural Network that can be trained to learn and generate extremely realistic human faces. To find out whether the recent developments in deep learning can help me answer my question, I tried to focus on improving the player faces in FIFA using the (in?)famous deepfakes algorithm. soccer) being my favorite sport, FIFA becomes the natural game of choice for all of my deep learning experiments.
However, with the massive advancements made in the field of image processing using Deep Neural Networks, is it time we can leverage that to improve the graphics while simultaneously also reducing the efforts required to create them? Let us try to answer that using the game FIFA 18…įootball (i.e. While the graphics have looked amazingly realistic in the last few years, it is still easy to distinguish them from the real world. Game Studios spend millions of dollars and thousands of development hours designing game graphics in trying to make them look as close to reality as possible. Comparison of Cristiano Ronaldo’s face, with the left one from FIFA 18 and the right one generated by a Deep Neural Network.
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