Fake videos of real people -- and how to spot them | Supasorn Suwajanakorn

1,285,658 views ・ 2018-07-25

TED


Please double-click on the English subtitles below to play the video.

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Look at these images.
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Now, tell me which Obama here is real.
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(Video) Barack Obama: To help families refinance their homes,
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to invest in things like high-tech manufacturing,
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clean energy
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and the infrastructure that creates good new jobs.
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Supasorn Suwajanakorn: Anyone?
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The answer is none of them.
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(Laughter)
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None of these is actually real.
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So let me tell you how we got here.
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My inspiration for this work
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was a project meant to preserve our last chance for learning about the Holocaust
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from the survivors.
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It's called New Dimensions in Testimony,
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and it allows you to have interactive conversations
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with a hologram of a real Holocaust survivor.
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(Video) Man: How did you survive the Holocaust?
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(Video) Hologram: How did I survive?
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I survived,
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I believe,
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because providence watched over me.
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SS: Turns out these answers were prerecorded in a studio.
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Yet the effect is astounding.
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You feel so connected to his story and to him as a person.
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I think there's something special about human interaction
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that makes it much more profound
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and personal
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than what books or lectures or movies could ever teach us.
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So I saw this and began to wonder,
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can we create a model like this for anyone?
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A model that looks, talks and acts just like them?
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So I set out to see if this could be done
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and eventually came up with a new solution
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that can build a model of a person using nothing but these:
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existing photos and videos of a person.
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If you can leverage this kind of passive information,
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just photos and video that are out there,
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that's the key to scaling to anyone.
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By the way, here's Richard Feynman,
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who in addition to being a Nobel Prize winner in physics
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was also known as a legendary teacher.
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Wouldn't it be great if we could bring him back
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to give his lectures and inspire millions of kids,
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perhaps not just in English but in any language?
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Or if you could ask our grandparents for advice and hear those comforting words
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even if they're no longer with us?
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Or maybe using this tool, book authors, alive or not,
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could read aloud all of their books for anyone interested.
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The creative possibilities here are endless,
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and to me, that's very exciting.
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And here's how it's working so far.
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First, we introduce a new technique
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that can reconstruct a high-detailed 3D face model from any image
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without ever 3D-scanning the person.
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And here's the same output model from different views.
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This also works on videos,
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by running the same algorithm on each video frame
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and generating a moving 3D model.
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And here's the same output model from different angles.
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It turns out this problem is very challenging,
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but the key trick is that we are going to analyze
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a large photo collection of the person beforehand.
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For George W. Bush, we can just search on Google,
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and from that, we are able to build an average model,
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an iterative, refined model to recover the expression
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in fine details, like creases and wrinkles.
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What's fascinating about this
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is that the photo collection can come from your typical photos.
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It doesn't really matter what expression you're making
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or where you took those photos.
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What matters is that there are a lot of them.
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And we are still missing color here,
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so next, we develop a new blending technique
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that improves upon a single averaging method
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and produces sharp facial textures and colors.
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And this can be done for any expression.
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Now we have a control of a model of a person,
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and the way it's controlled now is by a sequence of static photos.
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Notice how the wrinkles come and go, depending on the expression.
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We can also use a video to drive the model.
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(Video) Daniel Craig: Right, but somehow,
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we've managed to attract some more amazing people.
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SS: And here's another fun demo.
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So what you see here are controllable models
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of people I built from their internet photos.
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Now, if you transfer the motion from the input video,
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we can actually drive the entire party.
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George W. Bush: It's a difficult bill to pass,
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because there's a lot of moving parts,
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and the legislative processes can be ugly.
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(Applause)
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SS: So coming back a little bit,
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our ultimate goal, rather, is to capture their mannerisms
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or the unique way each of these people talks and smiles.
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So to do that, can we actually teach the computer
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to imitate the way someone talks
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by only showing it video footage of the person?
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And what I did exactly was, I let a computer watch
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14 hours of pure Barack Obama giving addresses.
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And here's what we can produce given only his audio.
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(Video) BO: The results are clear.
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America's businesses have created 14.5 million new jobs
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over 75 straight months.
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SS: So what's being synthesized here is only the mouth region,
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and here's how we do it.
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Our pipeline uses a neural network
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to convert and input audio into these mouth points.
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(Video) BO: We get it through our job or through Medicare or Medicaid.
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SS: Then we synthesize the texture, enhance details and teeth,
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and blend it into the head and background from a source video.
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(Video) BO: Women can get free checkups,
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and you can't get charged more just for being a woman.
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Young people can stay on a parent's plan until they turn 26.
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SS: I think these results seem very realistic and intriguing,
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but at the same time frightening, even to me.
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Our goal was to build an accurate model of a person, not to misrepresent them.
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But one thing that concerns me is its potential for misuse.
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People have been thinking about this problem for a long time,
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since the days when Photoshop first hit the market.
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As a researcher, I'm also working on countermeasure technology,
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and I'm part of an ongoing effort at AI Foundation,
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which uses a combination of machine learning and human moderators
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to detect fake images and videos,
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fighting against my own work.
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And one of the tools we plan to release is called Reality Defender,
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which is a web-browser plug-in that can flag potentially fake content
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automatically, right in the browser.
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(Applause)
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Despite all this, though,
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fake videos could do a lot of damage,
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even before anyone has a chance to verify,
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so it's very important that we make everyone aware
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of what's currently possible
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so we can have the right assumption and be critical about what we see.
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There's still a long way to go before we can fully model individual people
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and before we can ensure the safety of this technology.
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But I'm excited and hopeful,
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because if we use it right and carefully,
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this tool can allow any individual's positive impact on the world
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to be massively scaled
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and really help shape our future the way we want it to be.
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Thank you.
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(Applause)
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