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What Is the Challenge for Deep Learning in Unconstrained Face Recognition?

机译:深度学习在无约束人脸识别中的挑战是什么?

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Recently deep learning has become dominant in face recognition and many other artificial intelligence areas. We raise a question: Can deep learning truly solve the face recognition problem? If not, what is the challenge for deep learning methods in face recognition? We think that the face image quality issue might be one of the challenges for deep learning, especially in unconstrained face recognition. To investigate the problem, we partition face images into different qualities, and evaluate the recognition performance, using the state-of-the-art deep networks. Some interesting results are obtained, and our studies can show directions to promote the deep learning methods towards high-accuracy and practical use in solving the hard problem of unconstrained face recognition.
机译:最近,深度学习已在面部识别和许多其他人工智能领域中占主导地位。我们提出一个问题:深度学习能否真正解决人脸识别问题?如果不是这样,深度学习方法在人脸识别方面的挑战是什么?我们认为人脸图像质量问题可能是深度学习的挑战之一,尤其是在无约束的人脸识别中。为了研究该问题,我们使用最新的深度网络将面部图像划分为不同的质量,并评估识别性能。取得了一些有趣的结果,我们的研究可以为指导深度学习方法朝着高精度和实际应用的方向发展,以解决人脸识别不受约束的难题。

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