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Ondřej Texler

GenAI Researcher       HeyGen

PhD graduate       CTU in Prague


Short Bio

My entire research career has been revolving around generating realistically looking content given certain conditions, ranging from painterly images, animated stylized videos, to expressive photorealistic avatars with believable and controllable motion. I hold PhD in Computer Graphics, published over 10 papers at top venues such as CVPR or SIGGRAPH, have been cited over 250 times, have GitHub repositories with over 600 stars and 100 forks, co-invented 9 patents, created proof-of-concepts helping to raise multi-million seed round, shipped and released computer vision models and novel rendering pipelines currently generating millions of dollars in ARR, peer-reviewed tens of papers, won prizes such as the Best in Show Award at Real-Time Live SIGGRAPH or Joseph Fourier Prize, and gave invited talks and interviews at SIGGRAPH Now, ECCV, or BBC News.

Research Interests

Diffusion Models
Computer Vision
Generative AI
Computer Graphics

Detailed Bio

I obtained my PhD (as well as MSc and BSc) in Computer Graphics at CTU in Prague under the supervision of prof. Daniel Sýkora. My PhD focused on research into style transfer -- generating realistically looking paintings and animated movies; my extensive collaboration and several internships with Adobe Research, Snap Research, and Samsung Research America resulted in 8 publications and winning the Best in Show Award at Real-Time Live at SIGGRAPH 2020. Upon completing my PhD, I joined NEON, Samsung Research America as a senior research scientist where I focused my research into computer vision techniques to generate virtual humans with a particular emphasis on photorealism, resulting in 9 patents and CVPR publication. Then I joined Drip.Art (rebranded as comfy.org) as a founding research scientist to lead the research efforts into generative AI, diffusion models, synthesizing stylized videos given a text description, and propagating edits through the video; successfully helping to raise a seed investment round. Lastly, I joined HeyGen as a GenAI Researcher where I focus on research of core avatar rendering technology, including developing and shipping GAN-based models, UNET-based and transformer-based diffusion models, to enable highly-realistic, personalized, and expressive avatars, unlocking multi-million revenue streams.

News

  • [04/2024]: I am joining HeyGen as a Generative AI Researcher.
  • [04/2023]: I left Samsung and assumed a permanent position of a Founding Research Scientist at Drip.Art (rebranded as comfy.org).
  • [02/2023]: I joined Drip.Art (rebranded as comfy.org) as an external research advisor.
  • [03/2023]: Our Synthesizing Photorealistic Virtual Humans paper has been accepted to CVPR 2023!
  • [10/2022]: My National Interest Waiver Green Card application got approved!
  • [07/2022]: We filed 3 patents related to generating photorealistic virtual humans!
  • [01/2022]: I have been granted an O-1 U.S. visa in the science category.
  • [10/2021]: I have been awarded the Joseph Fourier Prize for my research on Style Transfer!
  • [07/2021]: I gave a talk at SIGGRAPH Now 2021!
  • [06/2021]: I was invited to give a talk at 2d3d.ai!
  • [04/2021]: I successfully defended my PhD thesis!
  • [03/2021]: I moved to California, and started a full-time position at NEON, Samsung Research America!
  • [02/2021]: Our paper FaceBlit: Instant Real-time Example-based Style Transfer to Facial Videos has been accepted to i3D 2021.
  • [11/2020]: I gave a talk for BBC News Arabic regarding our latest research.
  • [10/2020]: Our paper StyleProp: Real-time Example-based Stylization of 3D Models has been accepted to PacificGraphics 2020, Wellington, New Zealand.
  • [8/2020]: We presented our paper Interactive Video Stylization Using Few-Shot Patch-Based Training at SIGGRAPH2020 full paper session, as a short oral at ECCV2020 Deep Internal Learning workshop, and at Siggraph RealTime Live, where we have won the Best in Show Award!
  • [6/2020]: Recently, I defended "a proposal of a dissertation thesis" and passed a Doctoral State Exam. I plan to finish my PhD in early 2021.
  • [5/2020]: Our paper Interactive Video Stylization Using Few-Shot Patch-Based Training has been accepted to SIGGRAPH 2020.
  • [4/2020]: For the rest of the year 2020, I am joining Samsung Research America, the NEON team!
  • [12/2019]: Our paper Arbitrary Style Transfer Using Neurally-Guided Patch-Based Synthesis has been accepted to Computers & Graphics journal.
  • [4/2019]: For Summer/Fall 2019 I will join Snap Research at Santa Monica, Los Angeles, CA.
  • [4/2019]: Our paper Stylizing Video by Example has been accepted to SIGGRAPH 2019, Los Angeles, CA.
  • [4/2019]: On 5-May I am presenting Enhancing Neural Style Transfer using Patch-Based Synthesis at Expressive 2019, Genoa, Italy.
  • [3/2019]: On 6-May I am presenting Fast Example-Based Stylization with Local Guidance at EuroGraphics 2019, Genoa, Italy.

Selected Patents

  • Hierarchical Model-based Generation of Images
    • O. Texler, D. Dinev, A. Gupta, H.J. Kang, A. Liot, S. Ravichandran, S. Sadi
    • US Patent US17/967,868, December 2023
  • Creating Images, Meshes, and Talking Animations from Mouth Shape Data
    • S. Ravichandran, A. Liot, D. Dinev, O. Texler, H.J. Kang, J. Palan, S. Sadi
    • US Patent US17/967,872, December 2023
  • Multimodal Disentanglement for Generating Virtual Human Avatars
    • S. Ravichandran, D. Dinev, O. Texler, A. Gupta, J. Palan, H.J. Kang, A. Liot, S. Sadi
    • US Patent US18/296,202, January 2024
  • End-to-end System for Synthesizing Talking Virtual Human Avatars
    • D. Dinev, O. Texler, S. Ravichandran, J. Palan, H.J. Kang, A. Gupta, A. Unnikrishnan, A. Liot, S. Sadi
    • US Patent App. 63/436,058, December 2022
  • Architecture for Using 1D Inputs in Image-2-Image Translation Networks
    • H.J. Kang, S. Ravichandran, O. Texler, D. Dinev, A. Liot, S. Sadi
    • US Patent App. 63/436,211, December 2022
  • High-fidelity Neural Rendering of Images
    • D. Dinev, S. Ravichandran, H.J. Kang, O. Texler, A. Liot, S. Sadi
    • US Patent App. 63/461,199, January 2024
  • Cache-based Content Distribution Network
    • A. Liot, A. Unnikrishnan, S. Sadi, S. Banerjee, V. Gokul, J. Palan, H.J. Kang, O. Texler
    • US Patent App. 63/453,825, January 2024
  • Lightweight Rendering System with on-device Resolution Improvement
    • R. Lokesh, S. Banerjee, H.J. Kang, O. Texler, S. Sadi
    • US Patent App. 63/456,337, January 2024

Talks & Interviews

  • SIGGRAPH Now 2021, invited talk  
  • 2d3d.ai, invited talk, 2021  
  • BBC News Arabic, interview, 2020  
  • RealTime Live!, session at SIGGRAPH 2020  
  • ECCV 2020, short oral  
  • SIGGRAPH 2020, paper session  
  • Expressive 2019, paper session
  • EuroGraphics 2019, paper session
  • CESCG 2018, paper session

Review Services

  • CAG 2025, Computers & Graphics
  • Qeios 2025
  • AI4CC @ CVPR 2024, AI for Content Creation Workshop
  • CAG 2024, Computers & Graphics
  • CTU in Prague 2024, Thesis Reviewer
  • WACV 2024, IEEE/CVF Winter Conference on Applications of Computer Vision
  • CAG 2023, Computers & Graphics
  • TVCG 2022, IEEE Transactions on Visualization and Computer Graphics
  • SIGGRAPH Asia 2022, ACM Transactions on Graphics
  • SIGGRAPH 2022, ACM Transactions on Graphics
  • SIGGRAPH Asia 2021, ACM Transactions on Graphics
  • Pacific Graphics 2021, Computer Graphics Forum

Publications

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Meet-In-Style: Text-driven Real-time Video Stylization using Diffusion Models

D. Kunz, O. Texler, D. Mould, and D. Sýkora

IEEE Computer Graphics and Applications, 2025

Project Page Paper Supplementary Video BibTeX
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3D Engine-ready Photorealistic Avatars via Dynamic Textures

Y. Wang, I. Molodetskikh, O. Texler, and D. Dinev

arXiv pre-print, 2025

Project Page Paper Supplementary Video BibTeX
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Synthesizing Photorealistic Virtual Humans Through Cross-modal Disentanglement

S. Ravichandran, O. Texler, D. Dinev, and HJ. Kang

IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

Project Page Paper Supplementary PDF BibTeX
CVPR video/project page [Only registered CVPR attendees]
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FaceBlit: Instant Real-time Example-based Style Transfer to Facial Videos

A. Texler, O. Texler, M. Kučera, M. Chai, and D. Sýkora

In Proceedings of the ACM in Computer Graphics and Interactive Techniques, 4(1), 2021 (I3D 2021)

Project Page Paper Supplementary Video Presentation BibTeX
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StyleProp: Real-time Example-based Stylization of 3D Models

F. Hauptfleisch, O. Texler, A. Texler, J. Křivánek, and D. Sýkora

In Computer Graphics Forum 39(7):575-586  (PacificGraphics 2020)

Project Page Paper Supplementary Video BibTeX
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Interactive Video Stylization Using Few-Shot Patch-Based Training

O. Texler, D. Futschik, M. Kučera, O. Jamriška, Š. Sochorová, M. Chai, S. Tulyakov, and D. Sýkora

In ACM Transactions on Graphics 39(4):73  (SIGGRAPH 2020), Best in Show Award at SIGGRAPH Real-Time Live!

Project Page Paper SIGGRAPH Talk GitHub Supplementary Presentation BibTeX
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Arbitrary Style Transfer Using Neurally-Guided Patch-Based Synthesis

O. Texler, D. Futschik, J. Fišer, M. Lukáč, J. Lu, E. Shechtman, and D. Sýkora

In Computers & Graphics 87:62-71  (January 2020)

Project Page Paper GitHub BibTeX
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Stylizing Video by Example

O. Jamriška, Š. Sochorová, O. Texler, M. Lukáč, J. Fišer, J. Lu, E. Shechtman, and D. Sýkora

In ACM Transactions on Graphics 38(4):107  (SIGGRAPH 2019, Los Angeles, California, July 2019)

Project Page Paper Supplementary Demo BibTeX
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Enhancing Neural Style Transfer using Patch-Based Synthesis

O. Texler, J. Fišer, M. Lukáč, J. Lu, E. Shechtman, and D. Sýkora

In Proceedings of the 8th ACM/EG Expressive Symposium, pp. 43-50  (Expressive 2019, Genoa, Italy, May 2019)

Project Page Paper GitHub Interactive Supplementary Presentation BibTeX
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StyleBlit: Fast Example-Based Stylization with Local Guidance

D. Sýkora, O. Jamriška, O. Texler, J. Fišer, M. Lukáč, J. Lu and E. Shechtman

In Computer Graphics Forum 38(2):83-91  (Eurographics 2019, Genoa, Italy, May 2019)

Project Page Paper GitHub Supplementary Presentation Unity3D Asset BibTeX
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Example-Based Stylization of Navigation Maps on Mobile Devices

O. Texler and D. Sýkora

In Proceedings of the 22nd Central European Seminar on Computer Graphics.  (CESCG 2018, Smolenice, Slovakia, 2018)

Paper Presentation

Education

  • 2018 ‒ 2021
    Doctoral degree study (PhD)

    Computer Graphics,
    FEE, CTU in Prague.

    Dissertation Thesis: Example-based Style Transfer.

  • 2016 ‒ 2018
    Master degree study (MSc)

    Computer Science,
    FIT, CTU in Prague.

    Master Thesis: Digital Image Processing and Image Stylization.

  • 2012 ‒ 2015
    Bachelor degree study (BSc)

    Computer Science,
    FIT, CTU in Prague.

    Bachelor Thesis: Architecture design and implementation of a large software system.

  • 2004 ‒ 2012
    High school

    Mathematics, Physics, and Descriptive Geometry specialization, Gymnasium of Christian Doppler.

Professional Experience

present
HeyGen, Los Angeles, California

Research & Development. Research of core avatar rendering technology. Developed a prototype deferred neural rendering pipeline, shipped several GAN-based avatar rendering models, including a novel scheme for fast training of highly-realistic and expressive avatars, researched UNet-based and transformer-based diffusion models, unlocking multi-million revenue streams.

GenAI Researcher
4/2024 ‒ present
Drip Artificial, San Francisco, California

Research & Development. (Rebranded as comfy.org) Leading the research efforts into developing an end-to-end Generative AI framework that allows for creating stylized videos based on a text prompt; in particular, text-to-video synthesis, example-based video style transfer, and propagating edits through the video sequence.

Founding Research Scientist
2/2023 ‒ 4/2024
Samsung Research America, California

Research & Development. Research and implementation of computer vision and deep learning techniques to render photorealistic virtual humans, focusing on faces. Involved conditional GANs, image-to-image translation networks, deferred neural rendering. Part of the NEON team.

Senior Research Scientist
3/2021 ‒ 4/2023
Samsung Research America, California

Research & Development. Research and implementation of various image-to-image and video-to-video translation neural networks for face manipulation, e.g., adding makeup, changing skin tone, adding or removing scars or wrinkles. Part of the NEON team.

Research Scientist Intern
4/2020 ‒ 2/2021
Snap Inc., Los Angeles, California

Research & Development. Research of new techniques on training generative adversarial networks for style transfer tasks; focused on a scenario where a minimal amount of data is available, and an interactive response is required. Furthermore, developing a shader-based real-time stylization for human portraits.

Research Scientist Intern
7/2019 ‒ 10/2019
Adobe Research, USA

Research & Development. Remote collaboration on several research projects, publications, and tech transfer project. Computer graphics; patch-based style transfer; neural-network-based style transfer.

Remote Collaboration
9/2017 ‒ 12/2019
Adobe Research, Seattle, Washington

Research & Development. Combining neural-network-based and patch-based style transfer methods. Chunk-based style transfer method with focus on a real-time performance.

Research Scientist Intern
7/2018 ‒ 10/2018
Adobe Research, San Jose, California

Research & Development. Guiding patch-based style transfer method using convolutional neural networks, image harmonization, and histogram optimization. Integrating developed style transfer method into Adobe Photoshop.

Research Scientist Intern
9/2017 ‒ 12/2017
Dynavix, Prague, Czechia

Software & Algorithm Engineer. Developing map-navigation app for smartphones. C++, Java (Android), JavaEE, Objective-C (iOS), C#.

Software Engineer
5/2014 ‒ 9/2017
World of Warcraft game server, Prague, Czechia

Software & Algorithm Engineer. The World of Warcraft game server. Extending game mechanics, scripting artificial intelligence, data-mining. C++, C#.

Software Engineer
2/2013 ‒ 5/2014
2013