本篇論文主要針對在複雜的環境光源下所拍攝的人臉，進行光源去除以及膚色還原
的功能。複雜的光源 (如: 遊樂場的昏暗環境中，各式機台所發出的光、夜店使用的七彩
燈、霓虹燈等) 映射在臉上，會讓人臉整體的膚色被強光顏色所覆蓋，而消除該類光源
顏色的方法，目前僅有使用 Photoshop 等修圖軟體進行人工編輯。進行此操作不僅
需要豐富的軟體知識以及影像處理知識，將人臉顏色修正也需要消耗不少的時間以及步
驟。為了能夠解決此問題，我們產生了一複雜光源的資料集，包含了複雜光源人臉以及
自然光源人臉作為輸入以及目標，並且提出了一使用 StyleGANV2 [2] 作為生成器的架
構，進一步去探索 StyleGAN Space 中每一個 Style Code，並針對了影響顏色的重點
Style Code 添加了 MLP 模組用於訓練顏色的對應，以及使用了 HyperNetwork 的架構
進一步的提升臉部細節的還原。本篇所提出的架構，能夠將在各式光源底下的人臉膚色
還原回來，且僅需 0.4 秒的執行時間。

This aper mainly focuses on the functions of light source removal and skin color
restoration for faces captured under complex ambient light sources. Complex light sources
(such as light from various machines in the dim environment of the layground, colorful
lights used in nightclubs, neon lights, etc.) are mapped on the face, which will make the
overall skin color of the face covered y strong light colors, while At resent, the only
way to eliminate the color of this type of light source is to use hoto editing software
such as Photoshop [1] for manual editing. This operation not only requires a wealth of
software knowledge and image rocessing knowledge, ut also requires a lot of time and
steps to correct the face color. In order to solve this roblem, we generated a dataset of
complex light sources, including faces with complex light sources and faces with natural
light sources as input and targets, and roposed an architecture using StyleGANV2 [2]
as a generator to further explore the hidden space of StyleGAN [2] In each Style Code,
and for the key Style Code that affects the color, an MLP module is added for training the
color correspondence, and the HyperNetwork architecture is used to further improve the
restoration of facial details. The architecture roposed in this article can restore the skin
color of the face under various light sources, and it only takes 0.4 seconds to inference.

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