3 Computer Vision News object manipulation and even satellite imagery. To address this, the team has built a detector that breaks down large satellite images into smaller patches, enhancing their resolution using super-resolution techniques and utilizing a multihead attention transformer network to extract textures and features to determine their authenticity. “We have very high accuracy rates, especially for multimodal and multidomain approaches,” Ilke reveals. “FakeCatcher has 96% accuracy, our multimodal detector has over 98%, and our satellite imagery detector has 99.62%. It’s getting better and better!” Ilke compares this work to an arms race–as the generators improve, so do the detectors, but then the generators improve again, and so on. It is an endless game of cat and mouse. However, she assures us the detectors are always one step ahead of any new generator, using authenticity signatures and priors in the data rather than conforming to fakery. We have to ask: What could go wrong? “I would say people can go wrong!” Ilke laughs. “Instead of using our technology to enhance decisionmaking, if people try to use it as the absolute decision-maker for validating fakes, then that’s bad. We’re not saying any of the detectors are 100% perfect. That’s why we provide so many different detectors. We don’t want to decide for you. The biggest risk is always humans because our systems are mostly deterministic, but humans arenot.” Trusted Media has also been building trust metrics around technical systems to enhance interpersonal trust, societal trust, Ilke Demir
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