Published February 23, 2026 | Version v1

StayStill: a large-scale 3D idle animation dataset

  • 1. ROR icon University of the Basque Country
  • 2. KTH Royal Institute of Technology
  • 3. ROR icon Electronic Arts (United States)

Description

Data: This repository contains the animation data presented in out paper [StayStill: a large-scale 3D idle animation dataset](https://arxiv.org/abs/2605.13693). StayStill is a dataset that contains around 650.000 frames of idle motion, encompassing general idle motion, idle motion while using a phone and idle actions. A more detailed overview of the data is explained in the [data](#data) section and in the original paper.

Related code: The code related to the dataset is available in our Github repository. This code can be used to automatically clean the data with the manual annotations and the code that we provide. It also enables to reproduce the results in the paper.

📖 Citing

If you use the StayStill dataset in any of your projects and scientific research, please cite it as follows:
bibtex
@article{landa2026staystill,
  author = {Atxa Landa, Eneko and Rodriguez, Igor and Lazkano, Elena and Kucherenko, Taras},
  title = {StayStill: a large-scale 3D idle animation dataset},
  journal = {Computer Graphics Forum},
  year = {2026}
}

🧍‍♂️Data

Train, validation and test splits

The official train, validation and test splits, as determined in our paper, are the following:

Split Subjects
Train 0 1 3 4 5 7 11 12 13 14 16 17 18 20 24 25 26 27 29 30 31 32 33 34 35 36 37 39 41 42 44 46 47 48 49
Validation 8 19 21 38 40
test 2 6 9 10 15 22 23 28 43 45

Detail

The data is divided into 2 folders:
- Freemocap: It contains the original skeleton provided by Freemocap (without the finger bones)
- Lafan: It contains the data retargeted and fitted to the LaFAN1 skeleton.

Each of these two folders has 3 subfolders:
- Idle: Contains 2 minutes long sequences of people idling
- Phone: Contains 2 minutes long sequences of people idling while using a phone
- Actions: Contains 18 different actions that are typical in idle scenarios

Each animation clip is named as so:

action_name[\_take_number]\_person_ID.bvh

The following table presents the data in a more specific manner:

Motion Type Action Name Nº of frames Duration (hh:mm:ss) Nº of clips
Idle action: look up/sky l_up 27.943 15:31 98
Idle action: look around l_aro 20.338 11:17 92
Idle action: look down/floor l_dow 17.817 09:53 85
Idle action: look shoes l_sho 15.623 08:40 75
Idle action: check watch l_wat 11.332 06:17 92
Idle action: check phone l_pho 21.237 11:47 89
Idle action: scratch head sc_hea 13.199 07:19 92
Idle action: scratch arm sc_arm 13.750 07:38 93
Idle action: scratch leg sc_leg 11.510 06:23 77
Idle action: scratch back sc_bac 10.900 06:03 66
Idle action: touch face/chin t_fac 14.852 08:15 93
Idle action: stretch arms st_arm 14.473 08:02 80
Idle action: stretch back st_bac 12.300 06:50 71
Idle action: rub eyes sc_eye 15.430 08:34 97
Idle action: yawn yaw 13,766 07:38 95
Idle action: look back (left) lb_lef 10.253 05:41 69
Idle action: look back (right) lb_rig 10.571 05:52 75
Idle action: balance l -> r wei_lr 11.100 06:10 48
Idle action: balance r -> l wei_rl 9.357 05:11 47
Idle actions total -- 275.751 2:33:11 1534
General Idle idle 181.846 1:41:01 50
Idle with a phone phone 187.741 1:44:18 50

 

📋 License

The provided dataset is released under the MIT License
You are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the dataset, under the conditions outlined in the MIT License.

See LICENSE.txt for the full license text.

Files

LICENSE.txt

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