Radim Špetlík is a PhD student in the Visual Recognition Group at the Czech Technical University, a co-founder and the chief technology officer of the start-up visionPigeon.ai (no longer active), the main developer and co-designer of the Mobile Game Xenofil (no longer available), and one of the three members of a team that placed first at the Angry Birds AI Competitions held on ECAI 2014 and IJCAI 2015, and third at IJCAI 2016.

Experience

Google LLC

Dec 2025 - Mar 2026

Google Student Researcher (3 month internship)

Internship at XR research group in San Jose. Project related to Google XR.

Applied Computer Vision s.r.o.

Jul 2019 - Present

Computer Vision R&D Consultant

CNN-based detectors, predictors, and classifiers were designed and trained. Python web backends for CV applications developed. Neural networks quantized and deployed on ARM devices. Contract work for companies such as iC Systems.ai.

visionPigeon s.r.o.

Jun 2021 - Sep 2024

Chief Technology Officer

Training and optimization of machine learning models for fashion e-commerce applications. Deployment on Azure cloud infrastructure. Design and implementation of annotation pipelines.

Microsoft Development Center Serbia

Jul 2018 - Sep 2018

Computer Vision Research PhD intern

Improvement of the iris verification pipeline used in Windows Hello both in terms of accuracy and speed.

Selected Publications

Spetlik, R., Pliska, M., Vrba, V., Matas, J.
HelixTrack: Event-Based Tracking and RPM Estimation of Propeller-like Objects.
To appear in the Findings track, CVPR 2026. #c++

Spetlik, R., Hlavsa, J., Čechová, J., Pojmanová, P., Matas, J., Urban, S.
Identity Verification from Human Scent using Channel Representation of 2D Gas Chromatography-Mass Spectrometry Data.
In Proceedings of Winter Conference on Applications of Computer Vision, 2026. (github) #python #highPerformanceComputing

Hlavsa, J., Spetlik, R., Čechová, J., Pojmanová, P., Matas, J., Urban, S.
Sex Classification from Human Scent Using Image Interpretation of 2D Gas Chromatography-Mass Spectrometry Data.
In Proceedings of Scandinavian Conference on Image Analysis, 2025. (available online, github) #python #highPerformanceComputing #leadership

Spetlik, R., Futschik, D., Sykora, D. (2025)
StructuReiser: A Structure-preserving Video Stylization Method.
In Computer Graphics Forum, 2025. (available online, github) #python #highPerformanceComputing

Spetlik, R., Matas, J. (2025)
Single-Image Localised Reflection Removal with k-Order Differences Term.
In Proceedings of Scandinavian Conference on Image Analysis, 2025. (available online, github) #python

Spetlik, R., Uhrova, T., Matas, J. (2025)
Efficient Real-Time Quadcopter Propeller Detection and Attribute Estimation with High-Resolution Event Camera.
In Proceedings of Scandinavian Conference on Image Analysis, 2025. (available online, github) #c++

Kolar, J., Spetlik, R, Matas, J. (2024)
EEPPR: Event-based Estimation of Periodic Phenomena Rate using Correlation in 3D.
In Proceedings of International Conference on Machine Vision, 2024. (available online) #leadership

Spetlik, R., Rozumnyi, D., Matas, J. (2024)
Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects with Denoising Diffusion Probabilistic Models.
In Proceedings of Winter Conference on Applications of Computer Vision, 2024. (available online) #python #highPerformanceComputing

Spetlik, R., Razumenic, I. (2019)
Iris Verification with Convolutional Neural Network and Unit-Circle Layer.
In Proceedings of German Conference on Pattern Recognition, 2019. (available online) #python

Spetlik, R., Franc, V., Cech, J. and Matas, J. (2018)
Visual Heart Rate Estimation with Convolutional Neural Network.
In Proceedings of British Machine Vision Conference, 2018. (available online) #python #biometry

Research Projects

Computer Vision Methods for Analysis of Two-dimensional Gas Chromatography

Developing computer vision techniques to analyze and interpret GC×GC–MS data, focusing on tasks such as sex, or blood type classification. (Jan 2023 - Present)

Periodic Phenomena Attribute Estimation

Measuring key properties — most importantly frequency or rate — of repeating physical processes using high-temporal-resolution event data. (Jun 2024 - Present)

Temporally Consistent Style Transfer

Applying an artistic style to video such that the output frames are not only visually consistent with the chosen style, but also stable across time. (Jul 2023 - Present)

Single-image Fast Moving Object Recovery

Reconstructing the appearance and structure of an object that appears blurred or distorted in a photograph due to fast motion during exposure. (Jul 2021 - Present)

Single-image Reflection Removal

Separating the transmitted scene (what lies behind glass) from reflections (unwanted secondary layers) in a photograph taken through a reflective surface. (Feb 2020 - Jan 2021)

Non-invasive Estimation of Blood Glucose Level

Inferring glucose levels using optical signals that correlate with blood composition; a cooperation with Czech Institute of Endocrinology. (Jun 2019 - Present)

Skills

Python (PyTorch, TF, NumPy) C / C++ CUDA Java Matlab Bash Grid Computing (SLURM, PBS) Azure Docker Git Camera Sync (Event, RGB-D, High-speed)

Education

  • PhD Degree
    2018 - Present, Czech Technical University in Prague
    Supervisor: prof. Ing. Jiří Matas, Ph.D
  • Master Degree (hons) in Computer Vision
    2016 - 2018, Czech Technical University in Prague
  • Bachelor Degree in Information Technology
    2013 - 2016, Czech Technical University in Prague
  • Bachelor Degree in General Studies & Humanities
    2010 - 2014, Charles University in Prague

Selected Awards

  • Rakathon - Hacker Community Prize
    Apr 2025
  • European Healthcare Hackathon - 2nd place
    Mar 2025
  • Chaos Neurathon - 1st place
    Nov 2023
  • IT SPY Best Master Thesis - Shortlisted
    2016 - 2018
  • Angry Birds AI Competition
    1st place (IJCAI 2015, ECAI 2014) • 3rd place (IJCAI 2016)