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------------
status: published
title: Brainwash Dataset
desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco
subdesc: The Brainwash dataset includes 11,917 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms
slug: brainwash
cssclass: dataset
image: assets/background.jpg
year: 2015
published: 2019-4-18
updated: 2019-4-22
authors: Adam Harvey
------------
## Brainwash Dataset
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### end sidebar
Brainwash is a dataset of livecam images taken from San Francisco's Brainwash Cafe. It includes 11,917 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throughout the entire day. The Brainwash dataset includes 3 full days of webcam images taken on October 27, November 13, and November 24 in 2014. According the author's [research paper](https://www.semanticscholar.org/paper/End-to-End-People-Detection-in-Crowded-Scenes-Stewart-Andriluka/1bd1645a629f1b612960ab9bba276afd4cf7c666) introducing the dataset, the images were acquired with the help of Angelcam.com. [^end_to_end]
The Brainwash dataset is unique because it uses images from a publicly available webcam that records people inside a privately owned business without any consent. No ordinary cafe customer would ever suspect that their image would end up in dataset used for surveillance research and development, but that is exactly what happened to customers at Brainwash cafe in San Francisco.
Although Brainwash appears to be a less popular dataset, it was notably used in 2016 and 2017 by researchers affiliated with the National University of Defense Technology in China for two [research](https://www.semanticscholar.org/paper/Localized-region-context-and-object-feature-fusion-Li-Dou/b02d31c640b0a31fb18c4f170d841d8e21ffb66c) [projects](https://www.semanticscholar.org/paper/A-Replacement-Algorithm-of-Non-Maximum-Suppression-Zhao-Wang/591a4bfa6380c9fcd5f3ae690e3ac5c09b7bf37b) on advancing the capabilities of object detection to more accurately isolate the target region in an image. [^localized_region_context] [^replacement_algorithm] The [National University of Defense Technology](https://en.wikipedia.org/wiki/National_University_of_Defense_Technology) is controlled by China's top military body, the Central Military Commission.
The Brainwash dataset also appears in a 2018 research paper affiliated with Megvii (Face++) that used images from Brainwash Cafe "to validate the generalization ability of [their] CrowdHuman dataset for head detection."[^crowdhuman]. Megvii is the parent company of Face++, who has provided surveillance technology to [monitor Uighur Muslims](https://www.nytimes.com/2019/04/14/technology/china-surveillance-artificial-intelligence-racial-profiling.html) in Xinjiang and may be [blacklisted](https://www.bloomberg.com/news/articles/2019-05-22/trump-weighs-blacklisting-two-chinese-surveillance-companies) in the United States.
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### Footnotes
[^readme]: "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385.
[^end_to_end]: Stewart, Russel. Andriluka, Mykhaylo. "End-to-end people detection in crowded scenes". 2016.
[^localized_region_context]: Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598.
[^replacement_algorithm]: Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.
[^crowdhuman]: Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, and Jian Sun. CrowdHuman: Benchmark for Detecting Human in a Crowd. 2018. http://arxiv.org/abs/1805.00123
journal = {CoRR},
volume = {abs/1805.00123},
year = {2018},
url = {},
archivePrefix = {arXiv},
eprint = {1805.00123},
timestamp = {Thu, 14 Mar 2019 14:56:07 +0100},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1805-00123},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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