Zurich, Switzerland

Tizian Lucien Zeltner

This inventor holds 1 USPTO granted patent and 5 published patent applications. Top assignee: Nvidia Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Tizian Lucien Zeltner. Retrieved from https://idiyas.com/inventor/tizian-lucien-zeltner

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Tizian Lucien Zeltner: Innovator in Real-Time Neural Appearance Models

Introduction

Tizian Lucien Zeltner is an inventive mind based in Zürich, Switzerland. He is known for his work in the field of real-time neural appearance models. His innovative approach utilizes advanced neural decoders to render scenes in real-time, achieving complex material appearances that were previously limited to offline processing.

Latest Patent Applications

Zeltner's notable patent application is titled "REAL-TIME NEURAL APPEARANCE MODELS." This application describes a method where learned hierarchical textures representing material properties are encoded as latent codes. When a ray intersects with geometry in a scene, the intersection point is mapped to one of these latent codes. The neural decoders then interpret the latent code to produce reflectance values and importance-sampled directions, which are essential for determining pixel colors.

Conclusion

Tizian Lucien Zeltner is an emerging inventor whose work in real-time neural appearance models showcases the potential of neural technology in rendering complex materials. His contributions to the field are noteworthy, and his ongoing research may lead to significant advancements in real-time graphics.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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