Introducing neural supersampling for real-time rendering - Facebook Research

Real-time rendering in virtual reality presents a unique set of challenges -- chief among them being the need to support photorealistic effects, achieve higher resolutions, and reach higher refresh rates than ever before. To address this challenge, researchers at Facebook Reality Labs developed DeepFocus, a rendering system we introduced in December 2018 that uses AI to create ultra-realistic visuals in varifocal headsets. This year at the virtual SIGGRAPH Conference, we're introducing the next chapter of this work, which unlocks a new milestone on our path to create future high-fidelity displays for VR. Our SIGGRAPH technical paper, entitled "Neural Supersampling for Real-time Rendering," introduces a machine learning approach that converts low-resolution input images to high-resolution outputs for real-time rendering. This upsampling process uses neural networks, training on the scene statistics, to restore sharp details while saving the computational overhead of rendering these details directly in real-time applications.