An All-In-One Convolutional Neural Network for Face Analysis
This work addresses the need for efficient and integrated face analysis systems, though it is incremental as it builds on existing multi-task learning frameworks.
The paper tackles the problem of performing multiple face analysis tasks simultaneously by introducing a single convolutional neural network that handles face detection, alignment, pose estimation, gender recognition, smile detection, age estimation, and face recognition, achieving state-of-the-art results for most tasks.
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.