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AssigneeAdobe Inc.
InventorsOliver Wang, Michal Lukac, Elya Shechtman, Mahyar Najibikohnehshahri
Estimating the term…
Techniques for using deep learning to facilitate patch-based image inpainting are described. In an example, a computer system hosts a neural network trained to generate, from an image, code vectors including features learned by the neural network and descriptive of patches. The image is received and contains a region of interest (e.g., a hole missing content). The computer system inputs it to the network and, in response, receives the code vectors. Each code vector is associated with a pixel in the image. Rather than comparing RGB values between patches, the computer system compares the code vector of a pixel inside the region to code vectors of pixels outside the region to find the best match based on a feature similarity measure (e.g., a cosine similarity). The pixel value of the pixel inside the region is set based on the pixel value of the matched pixel outside this region.
A computer-implemented method for patch-based image inpainting, comprising:
A computer system comprising:
A non-transitory computer-readable storage medium comprising instructions that, upon execution on a computer system, cause the computer system to perform operations comprising:
Dependencies are inferred from the claim text.