Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Xi Yin, Xiaoming Liu

Abstract

This paper explores multi-task learning (MTL) for face recognition. First, we propose a multi-task convolutional neural network (CNN) for face recognition, where identity classification is the main task and pose, illumination, and expression (PIE) estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weights to each side task, which solves the crucial problem of balancing between different tasks in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses in a joint framework. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the PIE variations from the learnt identity features. Extensive experiments on the entire multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in multi-PIE for face recognition. Our approach is also applicable to in-the-wild data sets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LF...Continue Reading

References

Jan 1, 2007·Plant Signaling & Behavior·Weihua Huang, Hai Huang
May 22, 2010·Proceedings of the ... International Conference on Automatic Face and Gesture Recognition·Ralph GrossSimon Baker
May 18, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Laurent El ShafeySébastien Marcel
Dec 3, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Yongquan ZhangJiabing Ji
Jan 17, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Changxing DingDacheng Tao
Apr 6, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Zhanpeng ZhangXiaoou Tang
Jun 23, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Dayong WangAnil K Jain

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