Deep Joint Face Hallucination and Recognition——阅读笔记
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1、In this paper, we address this problem by jointly learning a deep model for two tasks, i.e. face hallucination and recognition.
本文是连接两个任务模型:hallucination和recognition。
2、The recognition subnetwork are responsible for producing discriminative feature representations using the hallucinated images as inputs generated by hallucination sub-network.
recognition网络的输入就是hallucination网络的输出。
3、Empirical studies [14] in face recognition proved that a minimum face resolution between 32 × 32 and 64×64 is required for stand-alone recognition algorithms.
经验研究发现用于人脸识别算法的最小的人脸图像大小是32x32到64x64之间。
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