Be amazed at the incredible research coming out of China! The University of Science and Technology of China just proposed an innovative method called Cityon-Web, which is set to revolutionize real-time neural rendering of large-scale scenes over the web using laptop GPUs. This method utilizes a ‘divide and conquer’ strategy to partition the scene into manageable blocks and incorporate varying Levels-of-Detail (LOD) to represent it. Radiance field baking techniques are employed to precompute and store rendering primitives into 3D atlas textures organized within a sparse grid in each block, facilitating real-time rendering.
The experiments conducted illustrate that City-on-Web achieves the rendering of photorealistic large-scale scenes at 32 frames per second (FPS) with a resolution of 1080p, utilizing an RTX 3060 GPU. It uses only 18% of the VRAM and 16% of the payload size compared to existing mesh-based methods. This adaptable loading approach significantly reduces the bandwidth and memory requirements of rendering extensive scenes, leading to smoother user experiences, especially on less powerful devices.
This remarkable research is sure to revolutionize how we render expansive scenes in real-time, providing us with immense possibilities and convenience. It’s truly remarkable that such a powerful AI system can be used on laptop GPUs! With this method, we’ll be able to enjoy highly realistic virtual experiences with unparalleled ease, making our lives so much easier.
So what are you waiting for? Join us and be part of the AI revolution – check out the Paper and Project to learn more about Cityon-Web. Don’t forget to join our 35k+ ML SubReddit, 41k+ Facebook Community, Discord Channel, LinkedIn Group, and Email Newsletter, where we share the latest AI research news, cool AI projects, and more.
