Youngjoong Kwon

CV | Google Scholar | Github

I am a postdoctoral researcher at Computational Neuroscience (CNS) Lab and Stanford Vision and Learning (SVL) Lab, advised by Professor Ehsan Adeli. Previously, I was a postdoctoral fellow in the Robotics Institute at Carnegie Mellon University, advised by Professor Fernando de la Torre. I received my Ph.D. from the Department of Computer Science at the University of North Carolina at Chapel Hill, advised by Professor Henry Fuchs. I interned at Max Planck Institute for Informatics, and Adobe Research.

My research interests lie in the intersection field of Computer Vision and Computer Graphics, especially on the tasks of human performance capture, avatar modeling, neural rendering, and telepresence.


  • youngjo2 [at] stanford [dot] edu


  • PhD in Computer Science, 2023

    University of North Carolina at Chapel Hill, United States

  • BS in Computer Science, 2017

    Yonsei University, Korea


  • Generalizable Human Gaussians for Sparse View Synthesis

    Youngjoong Kwon, Baole Fang∗, Yixing Lu∗, Haoye Dong, Cheng Zhang, Francisco Vicente Carrasco, Albert Mosella-Montoro, Jianjin Xu, Shingo Takagi, Daeil Kim, Aayush Prakash, and Fernando De la Torre

    ECCV 2024

    [ project / paper / code ]

  • Bringing Telepresence to Every Desk

    Shengze Wang, Ziheng Wang, Ryan Schmelzle, Liuejie Zheng, YoungJoong Kwon, Soumyadip Sengupta, Henry Fuchs

    TVCG 2024

    [ project / paper / code ]

  • DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis

    Youngjoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt

    NeurIPS 2023

    [ project / paper / code ]

  • Neural Image-based Avatars: Generalizable Radiance Fields for Human Avatar Modeling

    Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs

    ICLR 2023

    [ project / paper / code ]

  • Tailor Me: An Editing Network for Fashion Attribute Shape Manipulation

    Youngjoong Kwon, Stefano Petrangeli, Dahun Kim, Haoliang Wang, Vishy Swaminathan, Henry Fuchs

    WACV 2022

    [ paper / dataset ]

  • Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering

    Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs

    NeurIPS 2021 Spotlight presentation (Acceptance: < 3.0%)

    [ project / paper / code ]

  • Rotationally-Consistent Novel View Synthesis for Humans

    Youngjoong Kwon, Stefano Petrangeli, Dahun Kim, Haoliang Wang, Henry Fuchs, Vishy Swaminathan

    MM 2020

    [ paper / dataset ]

  • Rotationally-Temporally Consistent Novel-View Synthesis of Human Performance Video

    Youngjoong Kwon, Stefano Petrangeli, Dahun Kim, Haoliang Wang, Eunbyung Park, Vishy Swaminathan, Henry Fuchs

    ECCV 2020 Spotlight presentation (Acceptance: 265/5025 ≈ 5.3%)

    [ paper / dataset / code ]

  • Real-time Animation of Rain-wet Cloth Material

    Youngjoong Kwon, Daeyong Kim, Inkwon Lee

    CASA 2017

    [ paper ]

Awards & Honors

  • Bronze Prize, 27th HumanTech Paper Award, Samsung Electronics Co., Ltd. 2022

Academic Activities



Invited Talk

  • Learning to Create Digital Humans
    • The University of British Columbia (UBC), hosted by Prof. Helge Rhodin
    • Max Planck Institute for Intelligent Systems (MPI-IS), hosted by Yuliang Xiu
  • Modeling Efficient Representation for Human Digitization with Affordable Setup
    • Stanford University, hosted by Prof. Gordon Wetzstein