Researchers at the Chinese University of Hong Kong have published the CelebFaces Attributes Dataset (CelebA), a heavily annotated data set of 202,599 images of 10,177 celebrities’ faces they compiled to spur computer vision research. The researchers annotated each image with 40 binary attributes, such as “wearing hat,” “oval face,” and “mustache,” so that facial recognition and detection algorithms can learn to identify facial attributes in unfamiliar images.
Teaching Computers to Recognize Faces
Joshua New is a senior policy analyst at the Center for Data Innovation. He has a background in government affairs, policy, and communication. Prior to joining the Center for Data Innovation, Joshua graduated from American University with degrees in C.L.E.G. (Communication, Legal Institutions, Economics, and Government) and Public Communication. His research focuses on methods of promoting innovative and emerging technologies as a means of improving the economy and quality of life. Follow Joshua on Twitter @Josh_A_New.
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