logo

For the Inventor, By the Inventor

Santa Clara, CA, United States of America

Vladlen Koltun

This inventor holds 19 USPTO granted patents and 5 published patent applications and 3 EPO patents, primarily in Deep Learning Applications. Top assignees: Intel Corporation, Robert Bosch. Active years: 2019-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Vladlen Koltun. Retrieved from https://idiyas.com/inventor/vladlen-koltun

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

USPTO Granted Patents = 19 

% Patents Active = 94.7

 

Average Co-Inventor Count = 2.9

ph-index = 2

Forward Citations = 20(Granted Patents)


Company Filing History:

goldMedal17 out of 56,322 
 
Intel Corporation
 patents
silverMedal1 out of 30,209 
 
Robert Bosch
 patents
where one patent can have more than one assignee

Years Active: 2019-2026

Loading Chart...
Loading Chart...
Areas of Expertise:
Dense Prediction
Depth Estimation
Neural Reflectance Shaders
Geometric Model Fitting
Neural Network Classifiers
Graphics Rendering
Low-Light Imaging
Optical Flow Estimation
Convolutional Neural Networks
4D Cost Volume Processing
Deep Equilibrium Models
Speech Denoising
19 patents (USPTO):Explore Patents
1. 12646343 - Methods and apparatus to perform dense prediction using transformer blocks (2026-06-02),
2. 12400346 - Methods and apparatus for metric depth estimation using a monocular visual-inertial system (2025-08-26),
3. 12380714 - Methods and apparatus to perform dense prediction using transformer blocks (2025-08-05),
4. 12307579 - Deep geometric model fitting (2025-05-20),
5. 12260630 - Methods and apparatus to implement parallel architectures for neural network classifiers (2025-03-25),
6. 12260483 - Learning neural reflectance shaders from images (2025-03-25),
7. 12153416 - Mobile communication terminal device operation of robot terminal (2024-11-26),
8. 12094026 - Apparatus and method for enhancing graphics rendering photorealism (2024-09-17),
9. 11972519 - Learning neural reflectance shaders from images (2024-04-30),
10. 11928787 - Deep novel view synthesis from unstructured input (2024-03-12),
11. 11875252 - Neural network including a neural network projection layer configured for a summing parameter (2024-01-16),
12. 11816784 - Deep geometric model fitting (2023-11-14),
13. 11610129 - System and method for multiscale deep equilibrium models (2023-03-21),
14. 11393160 - Deep geometric model fitting (2022-07-19),
15. 10803565 - Low-light imaging using trained convolutional neural networks (2020-10-13),

Title: The Innovative Mind of Vladlen Koltun: Revolutionizing Neural Networks

Introduction: Vladlen Koltun, an influential inventor based in Santa Clara, California, has made significant contributions to the field of neural networks and geometric modeling. With a remarkable portfolio of 16 patents, he showcases his commitment to advancing technological innovations that enhance data processing capabilities.

Latest Patents: Among his latest patents, one titled "Deep Geometric Model Fitting" presents a sophisticated system that employs two neural networks to optimize and refine model weights. This innovative technology enables the generation of a geometric model from input data, significantly reducing dependency on the volume of data points. Another notable patent, "Methods and Apparatus to Implement Parallel Architectures for Neural Network Classifiers," outlines a framework for processing images using parallel neural network blocks, enabling enhanced classification accuracy through advanced data fusion and pooling techniques.

Career Highlights: Vladlen has had an impressive career working with prominent companies such as Intel Corporation and Robert Bosch GmbH. His tenure at these companies has allowed him to explore cutting-edge technologies, pushing the boundaries of what is possible within the realms of artificial intelligence and machine learning.

Collaborations: Throughout his career, Vladlen has collaborated with esteemed colleagues, including Qifeng Chen and Stephan Richter. These partnerships have fostered a creative environment that encourages innovative thinking and problem-solving in complex computational challenges.

Conclusion: Vladlen Koltun stands out as a pioneering inventor whose work continues to shape the future of neural networks and geometric modeling. His patents reflect a deep commitment to improving technology and tackling the challenges associated with data processing. As the field of artificial intelligence evolves, Vladlen's contributions will undoubtedly play a crucial role in driving further innovations and advancements.

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]
Loading…