Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Xiao-Shuai Hu

dblp:412/4495 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0009-5925-6899ORCID · reported

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

Graphics, 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 · 91% Virtual and augmented reality · 9%

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

TopicWeightPapersLastEvidence papers
Rendering › image-based rendering
light field display rendering
0.912025
Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025
Rendering › sampling
ray sampling
0.912025
Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025
Rendering
real-time rendering
0.912025
Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025
Virtual and augmented reality
3d display
0.312025
Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025

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

viewpoint mask texture · 0.9triangle culling · 0.9pixel culling · 0.9
YearPublicationVenuePosition
2025 Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display
abstract
Real-time rendering for light field displays (LFDs) enables human-computer three-dimensional (3D) interaction with smooth and realistic experience, which is potentially useful for 3D gaming, virtual reality, or surgical navigation. However, existing rendering methods realize a real-time rendering normally by sacrificing the 3D image resolution. We propose a culling-based real-time rendering (CBR) method with an accurate ray sampling, aimed at rendering the optimal synthetic images in real-time, which reproduce the high resolution 3D images. The synthetic image generation and display processes are first analyzed, identifying the condition of accurate ray sampling for generating the optimal synthetic images. Then the CBR method is proposed, significantly improving the generation speed of the optimal synthetic images under the accurate ray sampling condition by employing triangle culling in geometry shading stage and pixel culling using pre-computed viewpoint mask texture. Experiments show that accurate ray sampling generates the highest 3D image resolution, and the CBR method achieves superior frame rate, typically rendering 39.7 frames per second (fps) for a LFD with 4,225 viewpoints and a model of 16,301 triangle faces.
Xiao-Shuai Hu, Xing-Yu Lin, Yi-Jian Liu, Min-Hao Xiang, Yu-Qiang Guo, Qionghua Wang
IEEE Trans. Vis. Comput. Graph.1