Labeled Face Parts in the Wild is a dataset of photos used for face landmarking. The dataset was published in 2011 and contains 1,433 total images. Exposing.ai located 22 original photos from Flickr used to build LFPW.
Release 1 of LFPW consists of 1,432 faces from images downloaded from the web using simple text queries on sites such as google.com, flickr.com, and yahoo.com. Each image was labeled by three MTurk workers, and 29 fiducial points, shown below, are included in dataset. LFPW was originally described in the following publication:
Due to copyright issues, we cannot distribute image files in any format to anyone. Instead, we have made available a list of image URLs where you can download the images yourself. We realize that this makes it impossible to exactly compare numbers, as image links will slowly disappear over time, but we have no other option. This seems to be the way other large web-based databases seem to be evolving.
https://neerajkumar.org/databases/lfpw/
This research was performed at Kriegman-Belhumeur Vision Technologies and was funded by the CIA through the Office of the Chief Scientist. https://www.cs.cmu.edu/~peiyunh/topdown/ (nk_cvpr2011_faceparts.pdf)
To help understand how LFPW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Face Parts in the Wild was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.
If you reference or use any data from the Exposing.ai project, cite our original research as follows:
@online{Exposing.ai, author = {Harvey, Adam}, title = {Exposing.ai}, year = 2021, url = {https://exposing.ai}, urldate = {2021-01-01} }
If you reference or use any data from LFPW cite the author's work:
@inproceedings{Belhumeur2011LocalizingPO, author = "Belhumeur, Peter N. and Jacobs, David W. and Kriegman, David J. and Kumar, Neeraj", title = "Localizing parts of faces using a consensus of exemplars", booktitle = "CVPR", year = "2011" }