The topic of face-aging received increased attention by the computer vision community during the recent years. This interest is motivated by important real life applications where accurate age progression algorithms can be used. However, age progression methodologies may only be used in real applications provided that they have the ability to produce accurate age progressed images. Therefore it is of utmost importance to encourage the development of accurate age progression algorithms through the formulation of performance evaluation protocols that can be used for obtaining accurate performance evaluation results for different algorithms reported in the literature. In this paper we describe the organization of the, first ever, pilot independent age progression competition that aims to provide the basis of a robust framework for assessing age progression methodologies. The evaluation carried out involves the use of several machine-based and human-based indicators that were used for assessing eight age progression methods.