CPC G06T 5/70 (2024.01) [G06T 9/00 (2013.01); G06T 2207/20076 (2013.01)] | 18 Claims |
1. A method of automated image processing, comprising:
receiving an image and a diffusion model of the image;
generating a noise vector for the diffusion model by applying noise to the image;
encoding the image with a bias correction variable by using a conditional textual embedding of the diffusion model to generate an augmented diffusion model;
generating an augmented noise vector using the noise vector, the augmented diffusion model, and a latent trajectory optimization process, wherein generating the augmented noise vector comprises determining a plurality of diffusion trajectories at a plurality of steps between the image and the noise vector by minimizing a difference between the plurality of diffusion trajectories at the plurality of steps and one or more initial trajectories between the image and the noise vector; and
generating an output based on the augmented noise vector.
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