World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
11327
World Ranking
12370
National Ranking
5010

Overview

Jason Saragih is affiliated with Facebook in the United States and has contributed extensively to the fields of computer science and engineering. Their research has a strong focus on computer vision and pattern recognition, computational mechanics, and computer graphics and computer-aided design. They have also worked in related areas such as human-computer interaction and neurology.

The scientist's work covers a variety of topics, including face recognition and analysis, advanced vision and imaging, 3D shape modeling and analysis, generative adversarial networks and image synthesis, computer graphics and visualization techniques, human pose and action recognition, and facial nerve paralysis treatment and research.

Jason Saragih has authored a number of papers published in reputable venues. Some of their recent publications include:

  • Mixture of volumetric primitives for efficient neural rendering, 2021, ACM Transactions on Graphics
  • Authentic volumetric avatars from a phone scan, 2022, ACM Transactions on Graphics
  • Deep relightable appearance models for animatable faces, 2021, ACM Transactions on Graphics
  • The eyes have it, 2020, ACM Transactions on Graphics
  • Multiface: A Dataset for Neural Face Rendering, 2022, arXiv (Cornell University)

Frequent co-authors collaborating with Jason Saragih include:

  • Tomas Simon
  • Yaser Sheikh
  • Stephen Lombardi
  • Shih-En Wei
  • Gabriel Schwartz

The scientist frequently publishes their research in venues such as:

  • arXiv (Cornell University)
  • ACM Transactions on Graphics
  • Computer Graphics Forum
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Best Publications

  • The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

    Patrick Lucey;Jeffrey F. Cohn;Takeo Kanade;Jason Saragih

  • Deformable Model Fitting by Regularized Landmark Mean-Shift

    Jason M. Saragih;Simon Lucey;Jeffrey F. Cohn

  • Neural volumes: learning dynamic renderable volumes from images

    Stephen Lombardi;Tomas Simon;Jason Saragih;Gabriel Schwartz

  • PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

    Shunsuke Saito;Tomas Simon;Jason Saragih;Hanbyul Joo

  • Face alignment through subspace constrained mean-shifts

    Jason M. Saragih;Simon Lucey;Jeffrey F. Cohn

  • State of the Art on Neural Rendering

    Ayush Tewari;Ohad Fried;Justus Thies;Vincent Sitzmann

  • Deep appearance models for face rendering

    Stephen Lombardi;Jason Saragih;Tomas Simon;Yaser Sheikh

  • Mixture of volumetric primitives for efficient neural rendering

    Stephen Lombardi;Tomas Simon;Gabriel Schwartz;Michael Zollhoefer

  • A Nonlinear Discriminative Approach to AAM Fitting

    J. Saragih;R. Goecke

  • Authentic volumetric avatars from a phone scan

    Unknown

  • Person-independent facial expression detection using Constrained Local Models

    Sien. W. Chew;Patrick Lucey;Simon Lucey;Jason Saragih

  • Automated Facial Expression Recognition System

    Andrew Ryan;Jeffery F. Cohn;Simon Lucey;Jason Saragih

  • Modeling Facial Geometry Using Compositional VAEs

    Timur Bagautdinov;Chenglei Wu;Jason Saragih;Pascal Fua

  • SimPoE: Simulated Character Control for 3D Human Pose Estimation

    Ye Yuan;Shih-En Wei;Tomas Simon;Kris Kitani

  • VR facial animation via multiview image translation

    Shih-En Wei;Jason Saragih;Tomas Simon;Adam W. Harley

  • Real-time avatar animation from a single image

    Jason M. Saragih;Simon Lucey;Jeffrey F. Cohn

  • Learning AAM fitting through simulation

    Jason Saragih;Roland Göcke

  • Evaluating AAM fitting methods for facial expression recognition

    Akshay Asthana;Jason Saragih;Michael Wagner;Roland Goecke

  • Drivable Volumetric Avatars using Texel-Aligned Features

    Unknown

  • In the Pursuit of Effective Affective Computing: The Relationship Between Features and Registration

    S. W. Chew;P. Lucey;S. Lucey;J. Saragih

  • Learning Compositional Radiance Fields of Dynamic Human Heads

    Ziyan Wang;Timur Bagautdinov;Stephen Lombardi;Tomas Simon

  • Pixel Codec Avatars

    Shugao Ma;Tomas Simon;Jason Saragih;Dawei Wang

Frequent Co-Authors

Tomas Simon
Tomas Simon META Group
Yaser Sheikh
Yaser Sheikh Facebook (United States)
Simon Lucey
Simon Lucey University of Adelaide
Jeffrey F. Cohn
Jeffrey F. Cohn University of Pittsburgh
Fernando De la Torre
Fernando De la Torre Carnegie Mellon University
Michael Zollhöfer
Michael Zollhöfer Stanford University
Sridha Sridharan
Sridha Sridharan Queensland University of Technology
Roland Goecke
Roland Goecke University of New South Wales
Patrick Lucey
Patrick Lucey Stats Perform
Jun-Yan Zhu
Jun-Yan Zhu Carnegie Mellon University

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