Neural Outline Cache for Real-time Anti-aliasing Font Rendering

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Authors: Association for Artificial Intelligence 2026, Xiangqi Chen, Sang-Woon Jeon, Minglu Li, Jiashuaizi Mo, Hua Wang, Yanchao Wang, Zhonglong Zheng
Cited by: 0

Abstract

Neural textures have emerged as pivotal assets in next-generation neural rendering pipelines. However, hardware limitations and programming interface constraints lead to suboptimal performance in multi-instance real-time rendering scenarios. This bottleneck becomes particularly acute for texture-intensive tasks such as font rendering. To address this, we propose neural outline cache (NOC), a novel neural font representation supporting real-time anti-aliased rendering and procedural editing within modern neural graphics pipelines. NOC's lightweight network leverages multi-resolution hash encoding to cache spline-derived SDFs, delivering anti-aliased rendering via standard graphics pipelines. For massive-instance scalability, our cache buffer layout and batch-fused inference—tailored for NOC—eliminate neural texture binding bottlenecks. Benchmarks achieve 57.35 dB PSNR, 0.9980 SSIM, and 0.00116 MSE in offline rendering, while sustaining 0.51ms latency with 500 live instances. The integrated procedural node system enables real-time artistic font synthesis, certifying NOC as a production-grade neural asset.

Fields of Study & Subjects

Computer Graphics and Visualization Techniques Generative Adversarial Networks and Image Synthesis 3D Shape Modeling and Analysis

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN