Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines

Chi Nhan Duong¹, Khoa Luu², Kha Gia Quach¹, Tien D. Bui¹

¹Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada

²Computer Science and Computer Engineering Department, University of Arkansas, Fayetteville, AR, USA

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The AGFW database

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Please notice that this dataset is made available for academic research purpose only. Images in the database are collected from the Internet, and the copyright belongs to the original owners. If any of the images belongs to you and you would like it removed, please kindly inform us, we will remove it from our dataset immediately.
The cropped faces of AGFW is available here

Home

Comparisons

The AGFW database

BibTex and Citations

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More

The AginG Faces in the Wild (AGFW)

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In order to train the model and to analyze the aging effects, a large-scale dataset named AginG Faces in the Wild (AGFW) is collected. The AGFW consists of 36299 images with the age ranging from 10 to 64 years.

The database is collected from three sources:

The search engine using different keywords (i.e. "male 20 years old", etc.).
The Productive Aging Laboratory (PAL) database [1].
Mugshot images that are accessible from public domains.

Reference

[1] M. Minear and D. C. Park. A life span database of adult facial stimuli. Behavior Research Methods, Instruments, & Com- puters, 36(4):630–633, 2004.