We present a multi-purpose algorithm for simultaneous face detection, face alignment, pose estimation, gender recognition, smile detection, age estimation and face recognition using a single deep convolutional neural network (CNN). The proposed method employs a multi-task learning framework that regularizes the shared parameters of CNN and builds a synergy among different domains and tasks. Extensive experiments show that the network has a better understanding of face and achieves state-of-the-art result for most of these tasks.
Apart from learning identity-free expression-related features, Multi-task Learning (MTL) has been employed REF to simultaneously perform various face-related tasks including detection, alignment, pose estimation, gender recognition, age estimation, smile detection, and face recognition using a single deep CNN.
An All-In-One Convolutional Neural Network for Face Analysis
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
Computer Science