STAIR Actions

A Large-Scale Video Dataset of Everyday Human Actions

January 30, 2019: STAIR Actions v1.1 is released!

STAIR Actions is a video dataset consisting of 100 everyday human action categories.   Each category contains around 900 to 1800 trimmed video clips. Each clip lasts 5 to 6 seconds. Clips are taken from YouTube video or made by crowdsource workers.


SPEC (v1.1)

Train Validation Total
# of video clips 99,478 10,000 109,478
Avg. # of video clips
per category
1055.44 100 1,094.78
S.D. over categories 146.87 0 146.87
Min-Max 802-1,745 100-100 902-1,845

Comparison with other datasets (v1.1)

# of
# of
Avg. # of
videos per category
# of everyday
home actions
Overlapping w.r.t. STAIR Actions
STAIR Actions 100 109,478 1,094.78 100 ---
ActivityNet 203 849hrs 137 105 49 categories match 28 SA categories
Kinetics 400 300,000 750 215 122 categories match 54 SA categories
AVA 80 57,600 min=2,
80 40 categories match 43 SA categories

List of 100 Actions


Terms of Use

By downloading “STAIR Actions” (the Dataset), you agree to the following terms.

  • You will use the Dataset only for the purpose of AI research.
  • You will NOT distribute the Dataset or any parts thereof.
  • You will treat people appearing in the Dataset with respect and dignity.
  • The Dataset comes with no warranty or guarantee of any kind, and you accept full liability.


Assuming you agree the terms of use,

  • STAIR Actions metadata file (.json) is licensed under Creative Commons Attribution 4.0 International license (CC BY 4.0)  - (
  • The type field of STAIR Actions medata file (.json) indicates license condition of individual movie file by one character, where C, X, Y indicate Creative Commons CC0 Public Domain Dedication, ordinary YouTube license, CC BY, respectively.  - (


Download from GitHub

If you don’t agree the terms of use, please do not download.


Our Publication list

  • Yuya Yoshikawa, Jiaqing Lin, Akikazu Takeuchi, “STAIR Actions: A Video Dataset of Everyday Home Actions,” arXiv:1804.04326, Apr. 2018. [PDF]
  • 吉川友也, 竹内彰一, “家庭やオフィス内の動作認識用大規模動画データセットの構築,” 平成29年度人工知能学会全国大会 (JSAI2017), 2017.


If you use STAIR Actions dataset, please cite the following paper.

    author = {Yoshikawa, Yuya and Lin, Jiaqing and Takeuchi, Akikazu},
    title = {STAIR Actions: A Video Dataset of Everyday Home Actions},
    journal={arXiv preprint arXiv:1804.04326},
    url = {},
    year = {2018}
About us


Chiba Institute of Technology
Software Technology and Artificial Intelligence Research Laboratory (STAIR Lab)


  • Akikazu Takeuchi, STAIR Lab
  • Yuya Yoshikawa, STAIR Lab
  • Teruhisa Kamachi, Mokha Inc.
  • Hiroshi Ogino, Scaleout Inc.
  • Takahiro Tsutsumi, PlayNext Japan Inc.
  • Student volunteers in Chiba Institute of Technology, and many crowd workers


This work is supported by NEDO, Japan.


Akikazu Takeuchi
takeuchi at