Gothenburg, Sweden

Adam Lilja

This inventor holds 1 USPTO granted patent. Top assignee: Zenseact Ab. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Adam Lilja. Retrieved from https://idiyas.com/inventor/adam-lilja-nbos0cuh

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

Calculating rank

Average Co-Inventor Count = 1.0

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Adam Lilja and Road Geometry Estimation for Vehicles.

Introduction

Adam Lilja is an inventor based in Gothenburg, Sweden. His patent work includes a method for estimating road geometry and identifying road objects from vehicle camera images.

Latest Patents

Lilja is associated with 1 patent, titled “Road Geometry Estimation for Vehicles.” The invention describes a method that processes images from one or more vehicle cameras across consecutive time steps. Machine-learning algorithms encode the images into features representing visible road objects. The method transforms those features into a Bird’s Eye View (BEV) representation, then uses transformer-based algorithms to extract object embeddings. It decodes those embeddings to determine each road object’s position and class.

Career Highlights

Lilja is associated with Zenseact AB, a company working in vehicle technology. His patent describes a machine-learning approach to interpreting camera imagery and representing road objects around a vehicle.

Collaborations

The provided information names Junsheng Fu and Lars Hammarstrand as Lilja’s coworkers. Their specific roles in the patent or related work are not stated.

Conclusion

Adam Lilja’s patent presents a camera-based, machine-learning method for estimating road geometry and identifying road objects, reflecting his association with Zenseact AB.

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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