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Google made thousands of deepfakes to aid detection efforts
Google has released a data set of thousands of deepfake videos that it produced using paid, consenting ( ) actors in order to help researchers in the ongoing ( ) work of coming up with detection ( ) methods.
The data set, available on Github, contains more than 3,000 deepfake videos. To produce the videos, Google used 28 actors, placing pairs of them in quotidian ( ) settings：hugging, talking, expressing emotion and the like. To transform their faces, Google used publicly available, state-of-the-art ( ), automatic deepfake algorithms ( )：Deepfakes, Face2Face, FaceSwap and NeuralTextures.
Yet another data set of deepfakes is in the works, this one from Facebook. Earlier this month, it announced that it was launching ( ) a $10m deepfake detection project.
It will, as the name DeepFake Detection Challenge suggests, help people detect deepfakes. Like Google, Facebook’s going to make the data set available to researchers.
Google製作數千部「深度偽造」影片 助力辨識造假影像
Google已釋出一個內有數千部「深度偽造」影片的資料集，相關影像獲得付費演員同意產出，以協助研究者進行「深偽影片」辨識方法的研究。
這個資料集裡有超過3000部「深度偽造」影片，可透過（軟體開發平台）GitHub取得。為了製作這些影像，Google僱用28名演員，兩兩拍攝他們的日常動作：擁抱、交談、表達情緒等。Google使用可公開取得、最先進的自動化深偽演算法：「Deepfakes」、「Face2Face」、「FaceSwap」、「NeuralTextures」來改變演員的臉部。
不過也有另外一組「深度偽造」的資料集正在運作中，這是來自Facebook。本月初，Facebook甫宣布推出一項價值1000萬美元的深偽辨識專案。
Facebook公司將會如專案名稱深度偽造偵測挑戰所示，幫助人們找出深度偽造的作品。就像Google一樣，Facebook也要讓這些資料集可以讓研究者們來運用。
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An arbitrary face-swapping framework on images and videos with one single trained model! video pytorch faceswap gan swap face image-manipulation deepfakes ... ... <看更多>
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