11/23/2023 0 Comments Deep fake videoWhile the act of creating fake content is not new, deepfakes leverage powerful techniques from machine learning and artificial intelligence to manipulate or generate visual and audio content that can more easily deceive. ![]() Deepfakes are the manipulation of facial appearance through deep generative methods. You can practice trying to detect DeepFakes at Detect Fakes.Deepfakes ( portmanteau of " deep learning" and "fake" ) are synthetic media that have been digitally manipulated to replace one person's likeness convincingly with that of another. High-quality DeepFakes are not easy to discern, but with practice, people can build intuition for identifying what is fake and what is real. These eight questions are intended to help guide people looking through DeepFakes. Does the person blink enough or too much? But, DeepFakes may fail to make facial hair transformations fully natural. Does this facial hair look real? DeepFakes might add or remove a mustache, sideburns, or beard. Pay attention to the facial hair or lack thereof.Is there any glare? Is there too much glare? Does the angle of the glare change when the person moves? Once again, DeepFakes may fail to fully represent the natural physics of lighting. ![]() Do shadows appear in places that you would expect? DeepFakes may fail to fully represent the natural physics of a scene. Pay attention to the eyes and eyebrows.Does the skin appear too smooth or too wrinkly? Is the agedness of the skin similar to the agedness of the hair and eyes? DeepFakes may be incongruent on some dimensions. Pay attention to the cheeks and forehead.High-end DeepFake manipulations are almost always facial transformations. Nonetheless, there are several DeepFake artifacts that you can be on the look out for. When it comes to AI-manipulated media, there's no single tell-tale sign of how to spot a fake. The Detect Fakes experiment offers the opportunity to learn more about DeepFakes and see how well you can discern real from fake. The latest version of the website shows 32 videos that were produced as part of the Presidential Deepfakes Dataset. As such, we hosted a website called Detect Fakes to display thousands of the curated, high-quality DeepFake and real videos from the DFDC dataset publicly. ![]() We hypothesized that the exposure of how DeepFakes look and the experience of detecting subtle computational manipulations will increase people's ability to discern a wide-range of video manipulations in the future. Rather than fine-tune the best machine learning model for this Kaggle competition, we are curious about strategies and techniques for building public awareness of DeepFake technology and helping ordinary people think critically about the media that they consume. The goal of the challenge is to spur researchers around the world to build innovative new technologies that can help detect deepfakes and manipulated media." The winners of the Kaggle Competition were awarded $1,000,000. The description on the Kaggle Website explains, "AWS, Facebook, Microsoft, the Partnership on AI’s Media Integrity Steering Committee, and academics have come together to build the Deepfake Detection Challenge (DFDC). We already know DeepFakes can be quite believable, but just how believable are they? Kaggle's Deepfake Detection Challenge (DFDC) recently sought an algorithmic answer to this question of detecting fakes.
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