Age and gender estimation using deep residual learning network
Seok Hee Lee, Sepidehsadat Hosseini, Hyuk Jin Kwon, Jaewon Moon, Hyung Il Koo, Nam Ik Cho · 2018 International Workshop on Advanced Image Technology (IWAIT) · 2018
In this paper, we propose a deep residual learning model for age and gender estimation. Our method detects faces in input images, and then the age and gender of each face are estimated. The estimation method consists of three deep neural networks where we adopt residual learning methods. We train the model with IMDB-WIKI database [4]. However, since the database has only a small number of face images under the age of 20, we augment the set by collecting the images on the Internet. Experimental results show that the proposed model with residual learning yields improved performance.