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AssigneeAdobe Inc.
InventorsHareesh Ravi, Sachin Kelkar, Ajinkya Gorakhnath Kale
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The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating digital images by conditioning a diffusion neural network with input prompts. In particular, in one or more embodiments, the disclosed systems generate, utilizing a reverse diffusion model, an image noise representation from a first image prompt. Additionally, in some embodiments, the disclosed systems generate, utilizing a diffusion neural network conditioned with a first vector representation of the first image prompt, a first denoised image representation from the image noise representation. Moreover, in some embodiments, the disclosed systems generate, utilizing the diffusion neural network conditioned with a second vector representation of a second image prompt, a second denoised image representation from the image noise representation. Furthermore, in some embodiments, the disclosed systems combine the first denoised image representation and the second denoised image representation to generate a digital image.
A computer-implemented method comprising:
A system comprising:
A non-transitory computer-readable medium storing executable instructions that, when executed by a processing device, cause the processing device to perform operations comprising:
Dependencies are inferred from the claim text.