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AI DEEPFAKE APP SOFTWARE
The methodology of deepfake software such as DeepFaceLab and FaceSwap is well-served by a typical webcam environment, and removes many of the obstacles to authenticity that can still plague off-line deepfakes.įor instance, deepfakes perform less convincingly when the user turns to profile (or looks up), moves rapidly, or is subject to scene changes or sudden changes of lighting.
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In 2020 the Avatarify app announced deepfake celebrity webcam functionality, but at a quality significantly lower than the standard set by DeepFaceLab, which is now the repository of choice for recent headline-grabbing Tom Cruise deepfaker Chris Ume, as well as high-level film and TV production companies around the world.ĭeepFaceLab, the seed application for DeepFaceLive and the reported (Russian language) framework for 95% of all the deepfakes on YouTube, is also the software used by Shamook, the deepfaker whose extraordinary work on improving Luke Skywalker’s guest appearance in The Mandalorian recently inspired Lucasfilm to hire him as a VFX consultant. The possibility of ‘deepfake cam girls’ emerged in the media a couple of years ago. Possible UsesĬommenters in a thread (Russian language) at Russian social site VK.com speculate on the possible uses of DeepFaceLive, and seem to have discerned all the likely applications for the software: as an ‘anonymization’ or recreational filter in Zoom and similar applications as a means for committing fraud or deceiving the person watching the live stream and – perhaps most likely, in light of the software’s provenance and user-base – as a means of implementing celebrity-focused webcam-based sex work (see image at end of article). The DeepFaceLab GitHub has been forked over 6,000 times, while the new DeepFaceLive currently has 85 forks. Users report that DeepFaceLive is extremely demanding in terms of hardware resources, but Petrov has responded to this by asserting that DeepFaceLive is intended for well-specced PCs in an indoor environment.
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Most ‘A’ sets are usually of a single individual. Here we see that the source dataset is extremely diverse, apparently with the intent of creating a robust and well-generalized model that can transform a wide range of facial types into the image of the Australian actress.
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Training the Margot Robbie model – an image posted at the DeepFaceLab/DeepFaceLive Discord by Ivan Petrov. On a graphics card with 4GB of VRAM, it also requires 32GB of swap disk space. Comments on the Discord server confirm that these can also be implemented in DeepFaceLive.ĭeepFaceLive currently supports only NVIDIA GPUs, with the GTX 750 the lowest hardware that can obtain a reasonable result with the application. However, DeepFaceLab can also perform entire head swaps, a process which completely overwrites the source head, albeit with limitations in regard to hairstyles. When the user is relatively well-fitted to the celebrity, a convincing result can be obtained.Īs is evident in the last three Margot Robbie swaps in the images above, the software can’t perform miracles where the end-user’s face has radically different general characteristics. Though the best results will be obtained by training the end-user’s face against the target celebrity, the quality of the simulation seems to be in direct proportion to how closely the end user resembles the target.
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The model he loads in the video is hosted at mrdeepfakes, and has been used until now for offline deepfake processing. Vladislav Pedro using DeepFaceLive to transform himself into Tom Cruise in real time.