This new application of layered neural nets is about to make Photoshop amazing


“This looks Photoshopped.” How many times have you heard — or said — those three skeptical words? And yet every year, Photoshop and tools like it get a little more sophisticated, and it gets tougher to tell what’s a ‘shop and what’s not. More research comes out, more programs are written to incorporate the new research, and then artists get their hands on the tools and develop a deft and subtle touch.

Now a group of researchers from Cornell University and Adobe have layered neural nets atop an image style transfer AI, to create an even more powerful image manipulation tool they’re calling Deep Photo Style Transfer. It takes a reference image, often heavily stylized, and an input image. Then it clones the style of the reference image onto the input image. What it spits out at the end is startling because of how seamless the changes can be.

Left: input image. Center: reference image. Right: output image.

Using “semantic segmentation,” the authors teased apart the concepts of edges, textures, content, and style to build their neural nets. You can think of it as a combination of the magic wand tool and the heal tool from Photoshop, or perhaps as a “format painter” like the one in Microsoft Word except for photos. The study authors used their tool to swap the textures of apples, for example, and to change the weather and time of day in photos.

Semantic segmentation is most valuable in the way it can be tuned for whatever input image it receives. In a mathematical modeling…

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