臺灣博碩士論文加值系統

現今人臉驗證之應用非常廣泛，利用人臉驗證技術來簡化人力、蒐集數據與提供服務等，人臉驗證技術會變得如此熱門，與深度學習技術影像視覺上的突破有關。本研究使用生成對抗網路訓練卸妝系統，透過合成化妝影像增加訓練資料集，使用Stacked-hourgalss的方式堆疊Generator，將CycleGAN與人臉驗證系統結合一起訓練，設計出一個使用者畫上不同妝容時，一樣能精準完成人臉驗證之系統。

誌謝……………………………………………………………………….i
摘要………………………………………………………………………ii
ABSTRACT……………………………………………………………..iii
目錄……………………………………………………………………...iv
圖目錄…………………………………………………………………....v
表目錄…………………………………………………………………..vii
第一章 緒論……………………………………………………………...1
1.1 研究背景………………………………...………………………………………1
1.2 研究動機與目的………………………………………………………………...1
第二章 文獻探討…………………………………………………………...3
2.1 卸妝系統………………………………………………………………………...3
2.2 GAN……………………………………………………………………………..3
2.3 CycleGAN……………………………………………………………………….5
第三章 研究設計…………………………………………………………...7
3.1 研究流程………………………………………………………………………...7
3.2 資料集之設計…………………………………………………………………...7
3.3 研究架構………………………………………………………………………...9
3.4 人臉驗證……………………………………………………………………….14
第四章 研究結果 16
4.1 pretrain………………………………………………………………………….16
4.2 1st fine-tune…………………………………………………………………….19
4.3 2st fine-tune…………………………………………………………………….21
4.4 Stacked-hourgalss………………………………………………………………23
4.5 人臉驗證……………………………………………………………………….24
第五章 結論與未來展望…………………………………..……………….26
5.1 結論…………………………………………………………………………….26
5.2 未來展望……………………………………………………………………….26
參考文獻 28

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