Deep cascaded Bi-network for face hallucination
Refereed conference paper presented and published in conference proceedings

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摘要We present a novel framework for hallucinating faces of unconstrained poses and with very low resolution (face size as small as 5pxIOD). In contrast to existing studies that mostly ignore or assume pre-aligned face spatial configuration (e.g. facial landmarks localization or dense correspondence field), we alternatingly optimize two complementary tasks, namely face hallucination and dense correspondence field estimation, in a unified framework. In addition, we propose a new gated deep bi-network that contains two functionality-specialized branches to recover different levels of texture details. Extensive experiments demonstrate that such formulation allows exceptional hallucination quality on in-the-wild low-res faces with significant pose and illumination variations.
著者Zhu S., Liu S., Loy C.C., Tang X.
會議名稱European Conference on Computer
會議開始日08.10.2016
會議完結日16.10.2016
會議地點Amsterdam
會議國家/地區荷蘭
會議論文集題名ECCV 2016: Computer Vision – ECCV 2016
詳細描述organized by University of Amsterdam,
出版年份2016
月份1
日期1
卷號9909 LNCS
出版社Springer Verlag
出版地Germany
頁次614 - 630
國際標準書號9783319464534
國際標準期刊號1611-3349
語言英式英語

上次更新時間 2020-09-08 於 04:36