AI synthetic anchor generation method, electronic device and readable storage medium
A generator and video frame technology, applied in biological neural network models, speech analysis, instruments, etc., can solve the problems of not having wide practicability, the unnatural combination of anchor voice and expression, and the inability to promote multiple speakers. Achieve the effect of small difference in details, high video quality, and easy to use
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[0040] The lip-sync network consists of a face encoder and an audio encoder, both consisting of a stack of 2D convolutional layers
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[0045] The video generator and each discriminator are trained sequentially through the following two stages:
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[0049] The adversarial loss calculation of the frame discriminator is shown in formula (3):
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[0052] The feature matching loss calculation of the frame discriminator is shown in formula (4):
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[0060] L
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[0062] In formula (6), L represents the length of the time interval for generating the adversarial loss, and J represents the video in the time length [t-L, t]
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[0069] Through the face key point detection, the obtained eye aspect ratio is used to calculate the blinking loss, and the blinking loss is used to train the vision.
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[0073] Adversarial training using temporal adversarial loss, L1 reconstruction loss, lip sync loss, and blink loss ...
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