arXiv (Cornell University) · 2020 · 14 citations · 8 references
ComputingComputer ScienceArtificial IntelligenceComputer GraphicsComputer VisionComputer Graphics HardwareDeep LearningGame PlayingGame-based LearningVideo Game StudiesArtificial Intelligence In GamesImage Super-resolutionSuper-resolutionSuper-resolution ImagingSuper-resolution ProcessingSuper-resolution RenderingVideo Game IndustryVideo Super-resolution
The computational cost of video game graphics is increasing and hardware for processing graphics is struggling to keep up. This means that computer scientists need to develop creative new ways to improve the performance of graphical processing hardware. Deep learning techniques for video super-resolution can enable video games to have high quality graphics whilst offsetting much of the computational cost. These emerging technologies allow consumers to have improved performance and enjoyment from video games and have the potential to become standard within the game development industry.
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Video Super-Resolution With Convolutional Neural Networks
Armin Kappeler, Seunghwan Yoo, Qiqin Dai et al. · IEEE Transactions on Computational Imaging · 2016 · 672 citations
Detail-Revealing Deep Video Super-Resolution
Xin Tao, Hongyun Gao, Renjie Liao et al. · 2017 · 562 citations