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Dataset administrator: yhkwon@keti.re.kr

For questions about access requests or the dataset, contact the administrator above.

Update (2026-11-09)

  • Updated the dataset administrator and support contact to yhkwon@keti.re.kr.
  • Revised the access instructions for requests through the Hugging Face dataset page, including applicant information, agreement confirmation, and administrator review.
  • Updated the dataset access link in this README to POLYGOM-STUDIO/2K2K.
  • Updated the preview image link to use assets hosted in this repository.

Update (2025-04-14)

File names were updated, and a simple sample loader based on Open3D was added.


Polygom2K2K Dataset

High-fidelity 3D Human Digitization from Single 2K Resolution Images

Sang-Hun Han, Min-Gyu Park, Ju Hong Yoon, Ju-Mi Kang, Young-Jae Park and Hae-Gon Jeon. CVPR 2023

[Project Page]

  • This repository provides new 2K2K dataset updated by Polygom.
  • Specifically, we provides same 1M mesehs of original 2K2K dataset with newly updated SMPLX parameters and registered SMPLX via non-rigid fitting.
  • Both SMPLX rigid and non-rigid fittings are simply optimized by noisy 3D keypoint and chamfer distance to the nearest point. Therefore noticable misalignment can be observed in some region (e.g. hair, hand, and foot). If you need accurately aligned SMPLX, please postprocess it.

2K2K reconstruction examples

Prerequisites

Please downalod "SMPLX_NEUTRAL.pkl" and "J_regressor_body25_smplx.txt" from SMPLX official repo

Then, place them into same directory

$MODEL_ROOT
  |-SMPLX_NEUTRAL.PKL
  |-J_regressor_body25_smplx.txt

$DATA_ROOT
  |- train
  |   |-1M
  |- test

Data explanation

Polygom2K2K includes 2,050(train 2000, test 50) high-fidility 3D body scans captured by 80 multi-view DSLR cameras by POLYGOM. Each scan is simplified to a maximum of 1M vertices. Scans with fewer than 1M vertices are provided in their raw form. The data is provided in PLY format, including vertex colors.

Additionally, we provide the results of SMPLX rigid fitting and SMPL (subdivided into 27554 vertices) non-rigid registration.

  1. Raw meshes are normalized in [0, 1] x [0, 1] x [0, 1] unit cube and centerd at (x0.5, y0.0, z0.5). (ground plane is xz plane and up-direction is +y.)

  2. SMPLX parameters from rigid fitting consist of "poses", "shapes", "expression", "Rh" (global orientation), and "Th" (global translation). Reconstruct it into mesh using the SMPLX layer then multiply "scale".

  3. SMPLX final meshes from non-rigid fitting are optimized by pytorch-nicp

Data access

  1. Sign in to Hugging Face and open the dataset page.

  2. Review the terms in the Agreement section below. Complete the access request form on the dataset page with your name, academic institution, email address, and intended use.

  3. Confirm that you have read and agree to the terms, then submit your request for administrator review.

For questions about access requests, contact yhkwon@keti.re.kr.

Preview data

We've uploaded sample loading code named "load_sample.py".

# pip install open3d required

python load_sample.py --data_root DATA_ROOT --model_root MODEL_ROOT

# e.g. python load_sample.py --data_root /media/ssd/2k2k --model_root /media/smplx

It will visualize overall sample one-by-one using Open3D visualizer.

Agreement

  1. The 2K2K dataset (the "Dataset") is available for non-commercial research purposes only. Any other use, in particular any use for commercial purposes, is prohibited. This includes, without limitation, incorporation in a commercial product, use in a commercial service, as training data for a commercial product, for commercial ergonomic analysis (e.g. product design, architectural design, etc.), or production of other artifacts for commercial purposes including, for example, web services, movies, television programs, mobile applications, or video games. The Dataset may not be used for pornographic purposes or to generate pornographic material whether commercial or not. The Dataset may not be reproduced, modified and/or made available in any form to any third party without POLYGOM’s prior written permission.

  2. You agree not to reproduce, modify, duplicate, copy, sell, trade, resell, or exploit any portion of the images and any portion of derived data in any form to any third party without POLYGOM’s prior written permission.

  3. You agree not to further copy, publish, or distribute any portion of the Dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the Dataset.

  4. POLYGOM reserves the right to terminate your access to the Dataset at any time.

Citation

If you use this dataset for your research, please consider citing:

@InProceedings{han2023Recon2K,
title={High-fidelity 3D Human Digitization from Single 2K Resolution Images},
author={Han, Sang-Hun and Park, Min-Gyu and Yoon, Ju Hong and Kang, Ju-Mi and Park, Young-Jae and Jeon, Hae-Gon},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR2023)},
month={June},
year={2023},
}

@Misc{easymocap,  
    title = {EasyMoCap - Make human motion capture easier.},
    howpublished = {Github},  
    year = {2021},
    url = {https://github.com/zju3dv/EasyMocap}
}
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