Computer Vision News 14 thinking around this. These debates are not new. They go all the way back to the invention of the camera. For instance, the filmmaker Errol Morris, who’s a really famous documentarian here in the United States, he was asking these questions about 15 years ago in essays he published in the New York Times. He concludes that photographs are really a social object. They’re only useful so far as you can ask questions. You can interrogate them. Those answers may be different, depending on the context. You’re never going to get some kind of objective truth out of it, which I think is a really important thing to understand. With so much content on the Internet, how are you able to ascertain what is fake and to what degree it is fake? A lot of my research in computer vision image processing has been about media forensics. It’s like, what’s the integrity of this image? Has it been altered in some way? Can you determine if it’s from a generative model? Developing algorithms like that. Now, what I think is interesting is that when we started to actually look at the Internet in more recent years using these algorithms basically everything is coming back as fake. I think there’s some interesting reasons. Computer vision people sort of know why I think right away. Think computational photography. The smartphone, my iPhone, has a really sophisticated AI pipeline. When I take a photo, I’m not really getting the raw pixels right off the sensor. What I’m getting is an AI reconstruction of what the camera thinks the scene should look like. It’s usually cleaned up. The lighting is being adjusted. There are lots of tricks you can play with superresolution to get a much higherquality image from a low-quality sensor. The lenses are cheap, so you’re going to correct for that. There are all of these things that are sort of textbook built into the cameras, but those are all modifications to the image. A lot of the classical techniques for detecting forgeries are flagging these images like they’re altered. The other thing we found is there’s a ton of fake stuff that’s obviously fake, like memes. Memes are edited images, but we love that. It’s not like it’s a secret that it’s edited. That’s why they’re effective. That’s so much more prevalent than anything that can be considered a photorealistic fake. That’s really interesting because why are we developing all these algorithms for detection when, at the end of the day, we know everything has been altered in some way? That’s the Internet. As an author, do you like writing about things connected to but separate in some way from your day-to-day research work? Computer Vision Book
RkJQdWJsaXNoZXIy NTc3NzU=