Use Case and High-Level Description

Fully convolutional network for simultaneous Age/Gender recognition. The network is able to recognize age of people in [18, 75] years old range, it is not applicable for children since their faces were not in the training set.

Validation Dataset - Internal

~20,000 unique subjects representing diverse ages, genders, and ethnicities.


Input Image Result

Female, 18.97

Male, 26.52

Male, 33.41


Metric Value
Rotation in-plane ±45˚
Rotation out-of-plane Yaw: ±45˚ / Pitch: ±45˚
Min object width 62 pixels
GFlops 0.094
MParams 2.138
Source framework Caffe*


Metric Value
Avg. age error 6.99 years
Gender accuracy 95.80%


Name: input, shape: [1x3x62x62] - An input image in [1xCxHxW] format. Expected color order is BGR.


  1. Name: age_conv3, shape: [1, 1, 1, 1] - Estimated age divided by 100.
  2. Name: prob, shape: [1, 2, 1, 1] - Softmax output across 2 type classes [female, male].

Legal Information

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