Adobe, Inc.

Sudeep Siddheshwar Katakol

Aliakbar Darabi

Taesung Park

Kevin Duarte

Siddharth Iyer

Ryan Joe Murdock

Embodiments of the present disclosure include obtaining an input image and an approximate mask that approximately indicates a foreground region of the input image. Some embodiments generate an unconditional mask of the foreground region based on the input image. A conditional mask of the foreground region is generated based on the input image and the approximate mask. Then, an output image is generated based on the unconditional mask and the conditional mask. In some cases, the output image includes the foreground region of the input image.

Background separation for guided generative models

A method for training a GAN to transfer lighting from a reference image to a source image includes: receiving the source image and the reference image; generating a lighting vector from the reference image; applying features of the source image and the lighting vector to a generative network of the GAN to create a generated image; applying features of the reference image and the lighting vector to a discriminative network of the GAN to update weights of the discriminative network; and applying features of the generated image and the lighting vector to the discriminative network to update weights of the generative network.

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ANN ARBOR, MI, United States of America

Sudeep Siddheshwar Katakol