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AssigneeAdobe Inc.
InventorsChristopher Tensmeyer, Vlad Morariu, Michael Brodie
Estimating the term…
This disclosure describes one or more embodiments of systems, non-transitory computer-readable media, and methods that can learn or identify a learned-initialization-latent vector for an initialization digital image and reconstruct a target digital image using an image-generating-neural network based on a modified version of the learned-initialization-latent vector. For example, the disclosed systems learn a learned-initialization-latent vector from an initialization image utilizing a high number (e.g., thousands) of learning iterations on an image-generating-neural network (e.g., a GAN). Then, the disclosed systems can modify the learned-initialization-latent vector (of the initialization image) to generate modified or reconstructed versions of target images using the image-generating-neural network. For instance, the disclosed systems utilize the learned-initialization-latent vector as a starting point to learn a learned-latent vector for a target image that an image-generating-neural network converts into a high-fidelity reconstruction of the target image (with a reduced number of learning iterations).
A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computing device to:
A system comprising:
A computer-implemented method comprising:
Dependencies are inferred from the claim text.