We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN). The proposed method called, Hyperface, fuses the intermediate layers of a deep CNN using a separate CNN and trains multi-task loss on the fused features. It exploits the synergy among the tasks which boosts up their individual performances. Extensive experiments show that the proposed method is able to capture both global and local information of faces and performs significantly better than many competitive algorithms for each of these four tasks.
['Rajeev Ranjan', 'Vishal M. Patel', 'Rama Chellappa']
HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition