DeepGamingAI's video: Faster AI For Fortnite To PUBG Graphics Conversion Game Futurology 23

This is episode of the video series "Game Futurology" covering the paper "Contrastive Learning for Unpaired Image-to-Image Translation" by Taesung Park, Alexei A. Efros, Richard Zhang and Jun-Yan Zhu. PDF: https://arxiv.org/pdf/2007.15651.pdf Project Page: http://taesung.me/ContrastiveUnpairedTranslation/ Github Code: https://github.com/taesungp/contrastive-unpaired-translation Game Futurology: This is a video series consisting of short 2-3 minute overview of research papers in the field of AI and Game Development. This series aims to ponder over what the future games might look like based on the latest academic research going on in the field today. Subscribe for more weekly videos! Abstract: In image translation settings, each patch in the output should reflect the content of the corresponding patch in the input, independent of domain. We propose a straightforward method for doing so -- maximizing mutual information between the two, using a framework based on contrastive learning. The method encourages two elements (corresponding patches) to map to a similar point in a learned feature space, relative to other elements (other patches) in the dataset, referred to as negatives. We explore several critical design choices for making contrastive learning effective in the image synthesis setting. Notably, we use a multilayer, patch-based approach, rather than operate on entire images. Furthermore, we draw negatives from within the input image itself, rather than from the rest of the dataset. We demonstrate that our framework enables one-sided translation in the unpaired image-to-image translation setting, while improving quality and reducing training time. In addition, our method can even be extended to the training setting where each "domain" is only a single image. Music Credits: https://www.fesliyanstudios.com/ ---------------------------------------------------------------- • YouTube - https://www.youtube.com/c/DeepGamingA... • Twitter - https://twitter.com/deepgamingai • Medium - https://medium.com/@chintan.t93 • GitHub - https://github.com/ChintanTrivedi --------------------------------------------------------------------