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Jiashuaizi Mo

dblp:290/6707 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2026
0000-0001-5801-0795ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 1 first-author · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Rendering · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering
antialiasing
1.012026
Neural Outline Cache for Real-time Anti-aliasing Font Rendering · AAAI 2026
Rendering › geometric rendering › vector graphics rendering
font rendering
1.012026
Neural Outline Cache for Real-time Anti-aliasing Font Rendering · AAAI 2026
Rendering
neural rendering
1.012026
Neural Outline Cache for Real-time Anti-aliasing Font Rendering · AAAI 2026

Methods — techniques the papers use, named apart from their topics

signed distance function · 1.0neural texture · 1.0multi-resolution hash encoding · 1.0
YearPublicationVenuePosition
2026 Neural Outline Cache for Real-time Anti-aliasing Font Rendering
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 texture 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 (CBL) and batch-fused inference (BFI), tailored for NOC, mitigate neural texture streaming bottlenecks. We constructed an evaluation dataset using five font styles. In offline rendering, our proposed method achieves overall average results of 57.35 dB PSNR, 0.998 SSIM, and 1.1584e-3 pixel RMSE, while maintaining approximately 0.5ms frame latency with 500 real-time instances. To demonstrate its versatility, we integrated a procedural editor for visual effects editing of NOC textures. These results all prove that NOC is a reliable, production-ready neural asset.
Jiashuaizi Mo, Sang-Woon Jeon, Hua Wang 0002, Xiangqi Chen, Minglu Li 0001, Zhonglong Zheng
AAAI1
2026 A cross-domain feature fusion network for nighttime drone-view object detection
Xiangqi Chen, Chengzhuan Yang, Jiashuaizi Mo, Li Zhao 0005, Zhonglong Zheng
Pattern Recognit.3
2024 CSPNeXt: A new efficient token hybrid backbone
Xiangqi Chen, Chengzhuan Yang, Jiashuaizi Mo, Hicham Karmouni, Yunliang Jiang, Zhonglong Zheng
Eng. Appl. Artif. Intell.3