Hanbyul (Han) Joo

Assistant Professor
Department of Computer Science and Engineering
Seoul National University (SNU)
Email: hbjoo-at-snu-ac-kr
Office: Rm 324 Bldg 302
[Google Scholar] [CV]

I am an assistant professor at Seoul National University (SNU) in the Department of Computer Science and Engineering. Before joining SNU, I was a Research Scientist at Facebook AI Research (FAIR), Menlo Park. I finished my Ph.D. in the Robotics Institute at Carnegie Mellon University, where I worked with Yaser Sheikh. During my PhD, I interned at Facebook Reality Labs, Pittsburgh (Summer and Fall, 2017) and Disney Research Zurich (Summer, 2015). I received my M.S. in EE and B.S. in CS at KAIST, Korea. I am a recipient of the Samsung Scholarship and the CVPR Best Student Paper Award in 2018.


NEW I am hiring research intern students. See more details here.

Research

The goal of my research is to endow machines and robots with the ability to perceive and understand human behaviors in 3D. Ultimately, I dream to build an AI system that can behave like humans in new environments and can interact with humans using a broad channel of nonverbal signals (kinesic signals or body languages). I pursue this direction by creating new tools in computer vision, machine learning, and computer graphics.

   
The Panoptic Studio
  SNU ParaHome
   MocapEve²

News

Students

Byungjun Kim (MS/PhD)
Jeonghwan Kim (MS/PhD)
Hyunsoo Cha (MS/PhD)
Jisoo Kim (MS/PhD)
Taeksoo Kim (MS/PhD)
Inhee Lee (MS/PhD)
Sangwon Beak (MS/PhD)
Jeonghyeon Na (MS/PhD)
Hyeonwoo Kim (MS/PhD)
Mingi Choi (MS/PhD)
Junyoung Lee (MS)
Jongbin Lim (Intern)
Minseong Kim (Intern)
Kyungwon Cho (Intern)
Wonjung Woo (Intern)
Siyoung Nam (Intern)

Alumni

Yonwoo Choi (MS)
Sookwan Han (Intern)
Sungjae Park (Intern)

Dataset/Library

SNU ParaHome

FrankMocap

CMU Panoptic Studio Dataset

OpenPose Library

Tutorial

DIY A Multiview Camera System: Panoptic Studio Teardown
Hanbyul Joo, Tomas Simon, Hyun Soo Park, Shohei Nobuhara, and Yaser Sheikh
In Conjunction with CVPR 2017
[Tutorial Page] [Video]

Publications

DAViD: Modeling Dynamic Affordance of 3D Objects using Pre-trained Video Diffusion Models
Hyeonwoo Kim, Sangwon Beak, Hanbyul Joo
In ICCV 2025
[Paper] [Project Page]
Learning 3D Object Spatial Relationships from Pre-trained 2D Diffusion Models
Sangwon Beak, Hyeonwoo Kim, Hanbyul Joo
In ICCV 2025
[Paper] [Project Page]
HairCUP: Hair Compositional Universal Prior for 3D Gaussian Avatars
Byungjun Kim, Shunsuke Saito, Giljoo Nam, Tomas Simon, Jason Saragih, Hanbyul Joo, Junxuan Li
In ICCV 2025
ParaHome: Parameterizing Everyday Home Activities Towards 3D Generative Modeling of Human-Object Interactions
Jeonghwan Kim*, Jisoo Kim*, Jeonghyeon Na, Hanbyul Joo
In CVPR 2025
[Paper] [Project Page] [Code/Dataset]
PERSE: Personalized 3D Generative Avatars from A Single Portrait
Hyunsoo Cha, Inhee Lee, Hanbyul Joo
In CVPR 2025
[Paper] [Project Page]
Target-Aware Video Diffusion Models
Taeksoo Kim, Hanbyul Joo
In arxiv 2025
[Paper] [Project Page]
Learning to Transfer Human Hand Skills for Robot Manipulations
Sungjae Park*, Seungho Lee*, Mingi Choi*, Jiye Lee, Jeonghwan Kim, Jisoo Kim, Hanbyul Joo
In CORL X-Embodiment Workshop 2024
[Paper] [Project Page]
GraspDiffusion: Synthesizing Realistic Whole-body Hand-Object Interaction
Patrick Kwon, Hanbyul Joo
In preprint, 2024
[Paper]
Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models
Hyeonwoo Kim*, Sookwan Han*, Patrick Kwon, Hanbyul Joo
In ECCV 2024 (Oral)
[Paper] [Project Page]
Guess The Unseen: Dynamic 3D Scene Reconstruction from Partial 2D Glimpses
Inhee Lee, Byungjun Kim, Hanbyul Joo
In CVPR 2024
[Paper] [Project Page] [Code]
PEGASUS: Personalized Generative 3D Avatars with Composable Attributes
Hyunsoo Cha, Byungjun Kim, Hanbyul Joo
In CVPR 2024
[Paper] [Project Page] [Code]
GALA: Generating Animatable Layered Assets from a Single Scan
Taeksoo Kim*, Byungjun Kim*, Shunsuke Saito, Hanbyul Joo
In CVPR 2024
[Paper] [Project Page] [Code]
Mocap Everyone Everywhere: Lightweight Motion Capture With Smartwatches and a Head-Mounted Camera
Jiye Lee, Hanbyul Joo
In CVPR 2024
[Paper] [Project Page] [Code]
CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images
Sookwan Han, Hanbyul Joo
In ICCV 2023 (Oral) - Acceptance ratio: 152/8260 = 1.8%
[Paper] [Project Page] [Code]
Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Models
Byungjun Kim*, Patrick Kwon*, Kwangho Lee, Myunggi Lee, Sookwan Han, Daesik Kim, Hanbyul Joo
In ICCV 2023 (Oral) - Acceptance ratio: 152/8260 = 1.8%
[arxiv] [Project Page] [Code]
NCHO: Unsupervised Learning for Neural 3D Composition of Humans and Objects
Taeksoo Kim, Shunsuke Saito, Hanbyul Joo
In ICCV 2023
[arxiv] [Project Page] [Code]
Locomotion-Action-Manipulation: Synthesizing Human-Scene Interactions in Complex 3D Environments
Jiye Lee, Hanbyul Joo
In ICCV 2023
[arxiv] [Project Page] [Code]
BANMo: Building Animatable 3D Neural Models from Many Casual Videos
Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan, Andrea Vedaldi, Hanbyul Joo
In CVPR 2022 (Oral) - Acceptance ratio: 344/8161 = 4.2%
[arxiv] [Project Page]
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Grauman et al.
In CVPR 2022 (Oral) - Acceptance ratio: 344/8161 = 4.2%
[Best Paper Award Finalist]
[arxiv] [Project Page]
Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion
Evonne Ng , Hanbyul Joo, Liwen Hu, Hao Li, Trevor Darrell, Angjoo Kanazawa, Shiry Ginosar
In CVPR 2022
[arxiv] [Project Page] [Code+Data]
Modeling Human Intention Inference in Continuous 3D Domains by Inverse Planning and Body Kinematics
Yingdong Qian, Marta Kryven, Tao Gao, Hanbyul Joo, Josh Tenenbaum
arXiv 2021
[arxiv]
D3D-HOI: Dynamic 3D Human-Object Interactions from Videos
Xiang Xu, Hanbyul Joo, Greg Mori, Manolis Savva
arXiv 2021
[arxiv] [Code/Data]
FrankMocap: A Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration
Yu Rong, Takaaki Shiratori, Hanbyul Joo
In ICCV 2021 Workshop
[arxiv] [Project Page] [Code]
Exemplar Fine-Tuning for 3D Human Model Fitting Towards In-the-Wild 3D Human Pose Estimation
Hanbyul Joo, Natalia Neverova, Andrea Vedaldi
3DV 2021 (Oral)
[arxiv] [Code/Dataset]
Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamics
Evonne Ng, Shiry Ginosar, Trevor Darrell, Hanbyul Joo
In CVPR 2021
[arxiv] [Project Page]
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
Benjamin Biggs, Seb Ehrhadt, Hanbyul Joo, Ben Graham, Andrea Vedaldi, David Novotny
In NeurIPS 2020   (Spotlight)
[arxiv] [Project Page]
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
Jason Y. Zhang*, Sam Pepose*, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa
In ECCV 2020
[arxiv] [Project Page]
PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
Shunsuke Saito, Tomas Simon, Jason Saragih, Hanbyul Joo
In CVPR 2020   (Oral)
[arxiv] [Project Page] [Code] [Colab Demo]
You2Me: Inferring Body Pose in Egocentric Video via First and Second Person Interactions
Evonne Ng, Donglai Xiang, Hanbyul Joo, Kristen Grauman
In CVPR 2020   (Oral)
[arxiv] [Project Page] [Code/Data]
Single-Network Whole-Body Pose Estimation
Gines Hidalgo, Yaadhav Raaj, Haroon Idrees, Donglai Xiang, Hanbyul Joo, Tomas Simon, Yaser Sheikh
In ICCV 2019
[arxiv] [OpenPose Training] [OpenPose]
Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction
Hanbyul Joo, Tomas Simon, Mina Cikara, Yaser Sheikh
In CVPR 2019   (Oral)
[arxiv] [Code/Dataset] [Video]
Monocular Total Capture: Posing Face, Body and Hands in the Wild
Donglai Xiang, Hanbyul Joo, Yaser Sheikh
In CVPR 2019   (Oral)
[arxiv] [Dataset and Code] [Video]
Sensing, Measuring, and Modeling Social Signals in Nonverbal Communication
Hanbyul Joo
PhD Thesis, Robotics Institute, Carnegie Mellon University, 2019
[PDF]
Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies
Hanbyul Joo, Tomas Simon, and Yaser Sheikh
In CVPR 2018   (Oral)  
[CVPR Best Student Paper Award]
[PDF] [Supplementary Material] [video] [Project Page]
Structure from Recurrent Motion: From Rigidity to Recurrency
Xiu Li, Hongdong Li, Hanbyul Joo, Yebin Liu, Yaser Sheikh
In CVPR 2018
[PDF]
Hand Keypoint Detection in Single Images using Multiview Bootstrapping
Tomas Simon, Hanbyul Joo, Iain Mattews, and Yaser Sheikh
In CVPR 2017
[arXiv] [Project Page] [Code] [Dataset]
Panoptic Studio: A Massively Multiview System for Social Interaction Capture
Hanbyul Joo, Tomas Simon, Xulong Li, Hao Liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh
In TPAMI 2017 (Extended version of ICCV15)
[published version] [arXiv version] [Dataset]
Panoptic Studio: A Massively Multiview System for Social Motion Capture
Hanbyul Joo, Hao Liu, Lei Tan, Lin Gui, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh
In ICCV 2015   (Oral)
[Paper(PDF)] [Supplementary Material] [Project Page]
Press Coverage:

MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction
Hanbyul Joo, Hyun Soo Park, and Yaser Sheikh
In CVPR 2014   ((Oral)
[Paper(PDF)] [Project Page] [Dataset]
Press Coverage: ...
Graph-based Shape Matching for Deformable Objects
Hanbyul Joo, Yekeun Jeong, Olivier Duchenne, and In So Kweon
In ICIP 2011
[Paper(PDF)]

Graph-Based Robust Shape Matching for Robotic Application
Hanbyul Joo, Yekeun Jeong, Olivier Duchenne, Seong-Young Ko, and In So Kweon
In ICRA 2009
[Paper(PDF)]

Talks

  • "Measuring and Modeling Human Motion"

    • Facebook AI Video Summit, June 2019.

  • "Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction"

  • "Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies"

  • "Measuring and Modeling Social Signals for Computational Behavioral Understanding"

    • UC Berkeley, BAIR, MAY 2018 (hosted by Prof. Jitendra Malik).
    • UT Austin, School of Computer Science, April 2018.
    • CMU, School of Computer Science, April 2018.
    • MIT, CSAIL, April 2018.
    • MIT, Media Lab, Nov 2017.

  • "The Panoptic Studio: A Massively Multiview System for Social Interaction Capture"

    • UC Berkeley, Computer Vision Group, Dec 2016 (hosted by Prof. Alexei A. Efros).
    • Stanford, Computer Vision and Geometry Lab (CVGL), Dec 2016 (hosted by Prof. Silvio Savarese).
    • Adobe Research, Dec 2016 (hosted by Dr. Joon-Young Lee).
    • ASSP4MI workshop of ICMI, Nov 2016.
    • CMU, Machine Learning Lunch Seminar, Oct 2016.
    • ICCV Oral Talk, Dec 2015 (video link).
    • CMU, VASC Seminar, Dec 2015.
    • ETH Zurich, Computer Vision and Geometry lab, Oct 2015 (hosted by Prof. Marc Pollefeys).
    • Seoul National University, June 2015 (hosted by Prof. Kyoung Mu Lee).
    • ETRI, CG Team, May 2015 (hosted by Dr. Seong-Jae Lim).
    • KAIST, May 2015 (hosted by Prof. In So Kweon).

  • "The Panoptic Studio (CVPR14)"

    • Graduate Seminar, Civil & Environmental Engineering, CMU, Feb 2015 (hosted by Prof. Hae Young Noh).
    • People Image Analysis Consortium, CMU, Nov 2014.
    • Reality Computing Meetup, Autodesk, Nov 2014.

  • "MAP Visibility Estimation for Large-Scale Dynamic 3D Reconstruction"

Press Coverage

Patents

  • Motion capture apparatus and method (Patent No.: US 8805024 B2)
    Hanbyul Joo, Seong-Jae Lim, Ji-Hyung Lee, Bon-Ki Koo

  • Method for automatic rigging and shape surface transfer of 3D standard mesh model based on muscle and nurbs by using parametric control (Patent No.: US 7171060 B2)
    Seong Jae Lim, Ho Won Kim, Hanbyul Joo, Bon Ki Koo

  • 3D model shape transformation method and apparatus (Patent Application No.: US 20120162217 A1)
    Seong-Jae Lim, Hanbyul Joo, Seung-Uk Yoon, Ji-Hyung Lee, Bon-Ki Koo.