Sergey Tulyakov

Welcome! I am a Principal Research Scientist heading the Creative Vision team at Snap Research. My work focuses on creating methods for manipulating the world via computer vision and machine learning. This includes 2D and 3D methods for photorealistic object manipulation and animation, video synthesis, prediction and retargeting. My work has been published as 30+ top conference papers, journals and patents resulting in multiple tech transfers, including Snapchat Pet Tracking and Real-time Neural Lenses (gender swap, baby face, real-time try-on and many others).

View my past experience

Before joining Snap Inc., I built the real-time face tracking and reconstruction engine behind facify.me. 2016, I was a research intern at Microsoft Research, Cambridge, UK, and worked with Sebastian Nowozin and Andrew Fitzgibbon on improving generative models. In 2017, I interned at NVIDIA with Ming-Yu Liu, Xiaodong Yang and Jan Kautz and worked on video generation.

I am a PhD graduate from the University of Trento, Italy, where I worked with Nicu Sebe at the Multimedia and Human Understanding Group MHUG. Before joining the MHUG group, I worked as a software engineer for six years.

I am looking for prospective interns and collaborators. If you are interested send me an email.

Media coverage:

Real-time try-on: FastCompany
Object & material reconstruction
Pet Tracking: The Sun, The Verge, Variety, CNet and others
Real-time Neural Lenses: CNet, BoredPanda, Newsweek, The Telegraph and others
Time Machine Lens: elite daily, Engadget, and others
Image Animation: Two-minute papers, Vice, The Next Web, and others

Contact: stulyakov@snap.com, sergey@stulyakov.com

CV Google Scholar

The ultimate goal of the Creative Vision group is to develop cutting edge computer vision, machine learning, graphics and natural language technology to unlock creativity of users and creators in a variety of products at Snap. Our work enables machines to see, understand and manipulate the world.

We focus on foundational models for image, video, 3D, 4D synthesis, animation, manipulation and foundational technology to make these models small, fast, accurate and personalized. We uses images, audio, videos, text, sketches as inputs and outputs.

I'm always looking for motivated and driven researchers! Feel free to reach out to me to know more.

July 2017 - Present:

Principal Research Scientist at Snap Research, Santa Monica, CA

Jan 2017 - Apr 2017:

Research Intern at NVIDIA Research, Santa Clara, CA

Aug 2016 - Nov 2016:

Research Intern at Microsoft Research, Cambridge, UK

July 2010 - Sept 2012:

Team and Project Lead at HiQo-Solutions, Minsk, Belarus

June 2006 - June 2010:

Software Engineer at Todes Ltd, Minsk, Belarus

Nov 2012 - Apr 2017:

PhD Canditate at The Univesity of Trento, Italy

Sept 2014 - Feb 2015:

Research intern at the Robotics Institute, Carnegie-Mellon University

Sept 2009 - July 2010:

MSc at the Belarusian State University of Intormatics and Radioelectronics

Sept 2004 - July 2009:

B.Eng at the Belarusian State University of Intormatics and Radioelectronics

Teaching Computers to Imagine with Deep Generative Models

University of Trento, Italy. November 19-26, 2019

Tutorial: Unlocking Creativity with Computer Vision: Representations for Animation, Stylization and Manipulation

June 20, CVPR Virtual 2021

Tutorial: Video Synthesis: Early Days and New Developments

October 20, ECCV 2022, Tel-Aviv, Israel

Unsupervised Volumetric Animation

Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov, Kyle Olszewski, Jian Ren, Hsin-Ying Lee, Menglei Chai, Sergey Tulyakov