用AI製作電影明星─例如Gal Gadot和Emma Watson的色情片！

“將明星或暗戀對象的照片後製或貼在寫真集上”此類常於ACG作品出現、
現實生活中亦偶有所聞的性幻想方式,在陪伴眾多世代的人們成長之後,
隨著科技進步與工具成本降低,或許會於不久的未來被慢慢遺忘─
因為,AI將會為我們迅速合成好新鮮熱辣的色情片!
(2017/12/12的原始文章因受檢舉而遭系統鎖定,詢問Pixnet客服後仍無法編輯,故移除違規內容後重po一篇)

從Gigazine看到的報導,reddit討論區的網友deepfakes,
幾週前於”CelebFakes”版上公開了數部主角分別為Gal Gadot、
Emma Watson、Maisie Williams、Scarlett Johansson、
Taylor Swift和Aubrey Plaza的色情流出影片;
令人訝異的是,這些看起來幾乎毫無破綻的影片並非真貨,
居然全都是由deepfakes這位非專業特效工作室出身的網友,
使用開放原始碼的機器學習軟體,搭配普通A片所合成出來的!

(以下內容引述自MOTHERBOARD)
…..According to deepfakes—who declined to give his identity to me to avoid public scrutiny—
the software is based on multiple open-source libraries, like Keras with TensorFlow backend.
To compile the celebrities’ faces, deepfakes said he used Google image search,
stock photos, and YouTube videos. Deep learning consists of networks of interconnected nodes
that autonomously run computations on input data. In this case,
he trained the algorithm on porn videos and Gal Gadot’s face.
After enough of this “training,” the nodes arrange themselves to complete a particular task,
like convincingly manipulating video on the fly….
…..Artificial intelligence researcher Alex Champandard told me in an email that a decent,
consumer-grade graphics card could process this effect in hours,
but a CPU would work just as well, only more slowly, over days…..
…..
…..Deepfakes told me he’s not a professional researcher,
just a programmer with an interest in machine learning….
…..“I just found a clever way to do face-swap,” he said, referring to his algorithm.
“With hundreds of face images,
I can easily generate millions of distorted images to train the network,” he said.
“After that if I feed the network someone else’s face,
the network will think it’s just another distorted image and try to make it look like the training face.”…..
…..In a comment thread on Reddit, deepfakes mentioned that he is using an algorithm similar
to one developed by Nvidia researchers that uses deep learning to, for example,
instantly turn a video of a summer scene into a winter one.
The Nvidia researchers who developed the algorithm declined to comment on this possible application…..
…..In almost all of the examples deepfakes has posted, the result isn’t perfect.
In the Gadot video, a box occasionally appeared around her face where the original image peeks through,
and her mouth and eyes don’t quite line up to the words the actress is saying—
but if you squint a little and suspend your belief, it might as well be Gadot;
other videos deepfakes have made are even more convincing…..
…..

根據MOTHERBOARD的文章內容,deepfakes所使用的幾乎都是免費工具,
包括Google推出的開放原始碼軟體TensorFlow,以及Python的類神經網路函式庫Keras,
素材來源則是Google圖片搜索、YouTube影片及圖庫照片(stock photos);
訪談中並未提及節點架構或訓練時間等細節,但根據相關研究者Alex Champandard估計,
一般消費等級的顯示卡約數小時可完成,用CPU運算大概是數天左右─
無論是工具還是時間的成本,其實都沒有想像的多呢!

相較於以往個人所知的VFX科技,現在的合成門檻實在已經低了不少,
文章中也提到了對於未來造假影片可能到處竄流的擔憂,
認為相關網路政策應該及早準備因應,並呼籲研究者開發辨識真假的技術;
不過比起會造成的負面問題,我倒認為這方面的技術對A片公司頗有價值─
比起販售單體女優,未來是否可能聘請不同身材、特色演員來拍攝”底帶”,
再以搭配不同人物頭像的組合方式來販售呢?
聘請低知名度的演出者不但成本較低,發片生產的速度也應該比較快,
短時間就能大量上市不同主題的作品;就算低知名度演員長的不合己意,
只要A片公司將合成的運算模型一起打包、像DMM Player那樣使用專屬程式,
透過點選同捆的物的臉部資料即可切換面容─且比起脫光衣服,
僅提供大量臉部照片就能得到報酬,想必這也更利於A片公司說服高品質的演出者加入;
若將電影明星、歌手等面部資料設為5星,加入轉蛋要素的話更是不得了,
怎麼想F/GO都完全不是對手啊 XD

以目前的一般硬體配備而言,由於仍須至少數小時的運算,
上面的空想恐怕還不太切實際…..但隨著硬體效能上升,
“看A片前抽個轉蛋”或”抽籤決定要哪個臉來搭配1日10回(ry)系列”等,
想必在不久的將來都將會實現啊~嘶!

deepfakes的幾個討論串如下:
https://www.reddit.com/r/CelebFakes/comments/7amgwl/gal_gadot_oc/
https://www.reddit.com/r/CelebFakes/comments/75gic3/oc_emma_watson/dpiny7r/
https://www.reddit.com/r/CelebFakes/comments/75ppji/maisie_williams_oc/dpprwqb/
https://www.reddit.com/r/CelebFakes/comments/75wzts/scarlett_johansson_oc/
https://www.reddit.com/r/CelebFakes/comments/7ab5b6/aubrey_plaza_oc/
https://www.reddit.com/r/CelebFakes/comments/6xjkbb/september_2017_request_thread/

deepfakes所上傳的一些範例(內含裸露影片,未滿18歲請勿點選):
http://typecurry.hostzi.com/AI/AIP.html
被檢舉就是因為Pixnet規定不能直接張貼露點內容,所以請移至其他網站觀看.