In the last few posts we mostly talked about binary image descriptors and the previous post in this line of works described our very own LATCH descriptor [1] and presented an evaluation of various binary and floating point image descriptors. In the current post we will shift our attention to the field of Deep Learning and present our work on Age and Gender classification from face image using Deep Convolutional Neural Networks [2].

Example images from the AdienceFaces benchmark

Our method was presented in the following paper:

Gil Levi and Tal Hassner, Age and Gender Classification using Convolutional Neural Networks, IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, June 2015.

For code, models and examples, please see our project page.

New! Tensor-Flow implementation of our method .

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