text stringlengths 22 176k |
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# Camera list with one line of data per camera: |
# CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[] |
# Number of cameras: 1 |
1 SIMPLE_PINHOLE 640 360 547.60042105445621 320 180 |
# Image list with two lines of data per image: |
# IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME |
# POINTS2D[] as (X, Y, POINT3D_ID) |
# Number of images: 360, mean observations per image: 1569.5472222222222 |
360 0.99852135769900441 -0.024049926768643138 -0.048007871828194909 0.0084819504766003185 -0.48294793191509466 1.257989538791719 -6.2614557938128534 1 0359.png |
491.00900268554688 155.75408935546875 36598 351.0673828125 204.97776794433594 37113 351.0673828125 204.97776794433594 37245 487.36233520507812 338.9498291015625 34957 471.46337890625 239.10935974121094 -1 296.47161865234375 126.94258117675781 -1 340.92263793945312 291.58804321289062 36600 14.357011795043945 271.9471130... |
359 0.99852488064089961 -0.02401673039943298 -0.04796690220254677 0.0083925976365765917 -0.48027543021958219 1.2528851261505631 -6.23227607793216 1 0358.png |
486.38302612304688 152.03623962402344 36598 351.17605590820312 204.14234924316406 37245 351.17605590820312 204.14234924316406 37113 297.24508666992188 126.39220428466797 -1 486.61761474609375 330.894775390625 34957 454.8115234375 50.942428588867188 37247 559.7952880859375 97.444854736328125 36601 597.458984375 223.7595... |
358 0.99853892096338304 -0.023909250478442341 -0.047737047399893658 0.0083393865710906026 -0.48047950331510975 1.2489357342019587 -6.2025911264134139 1 0357.png |
Splannequin Dataset
This dataset is a derivative work based on the Google Mannequin Challenge dataset. It has been processed and adapted for 3D Gaussian Splatting research on monocular mannequin challenge videos.
Dataset Description
The Splannequin dataset contains processed video sequences from frozen scenes, optimized for monocular depth estimation and 3D reconstruction tasks. Each sample includes frames extracted from the original Mannequin Challenge videos with additional preprocessing for splatting-based methods.
Usage
from datasets import load_dataset
# Load the dataset
data = load_dataset("chien90190/Splannequin")
Attribution & License
This dataset is derived from the MannequinChallenge dataset and is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).
Citation
If you use this dataset in your research, please cite both the original Mannequin Challenge work and this derived dataset:
Original Mannequin Challenge Dataset:
@inproceedings{li2019learning,
title={Learning the Depths of Moving People by Watching Frozen People},
author={Li, Zhengqi and Dekel, Tali and Cole, Forrester and Tucker, Richard and Snavely, Noah and Liu, Ce and Freeman, William T},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}
Splannequin Dataset:
@InProceedings{chien2026splannequin,
author = {Hao-Jen Chien, Yi-Chuan Huang, Chung-Ho Wu, Wei-Lun Chao, Yu-Lun Liu},
title = {Splannequin: Freezing Monocular Mannequin-Challenge Footage with Dual-Detection Splatting},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {March},
year = {2026},
}
Contact
For questions or issues regarding this dataset, please open an issue on the dataset repository page.
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