Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform
Yuning Gong, Yifei Liu, Yifan Zhan, Muyao Niu, Xueying Li, Yuanjun Liao, Jiaming Chen, Yuanyuan Gao, Jiaqi Chen, Minming Chen, Li Zhou, Yuning Zhang, Wei Wang, Xiaoqing Hou, Huaxi Huang, Shixiang Tang, Le Ma, Dingwen Zhang, Xue Yang, Junchi Yan, Yanchi Zhang, Yinqiang Zheng

TL;DR
Visionary is a web-native platform that enables real-time neural rendering with Gaussian Splatting, supporting dynamic content and generative models directly in the browser, thus simplifying deployment and experimentation.
Contribution
It introduces a standardized Gaussian Generator contract and WebGPU-based renderer, enabling plug-and-play algorithms and efficient, dynamic 3D Gaussian rendering in web environments.
Findings
Achieves superior rendering efficiency compared to existing Web viewers.
Supports multiple variants like neural avatars and style transfer.
Unifies inference and rendering for easier deployment.
Abstract
Neural rendering, particularly 3D Gaussian Splatting (3DGS), has evolved rapidly and become a key component for building world models. However, existing viewer solutions remain fragmented, heavy, or constrained by legacy pipelines, resulting in high deployment friction and limited support for dynamic content and generative models. In this work, we present Visionary, an open, web-native platform for real-time various Gaussian Splatting and meshes rendering. Built on an efficient WebGPU renderer with per-frame ONNX inference, Visionary enables dynamic neural processing while maintaining a lightweight, "click-to-run" browser experience. It introduces a standardized Gaussian Generator contract, which not only supports standard 3DGS rendering but also allows plug-and-play algorithms to generate or update Gaussians each frame. Such inference also enables us to apply feedforward generative…
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Generative Adversarial Networks and Image Synthesis · 3D Shape Modeling and Analysis
