(We originally posted this in 2021. You can read more of our original ideas in our archive.)
Problem: Photoshopping images effectively can take hours.
Solution: I recently stumbled upon a paper by Cornell researchers Fujun Luan, Sylvain Paris, Eli Shechtman, and Kavita Bala which describes “Deep Painterly Harmonization.” As they describe,
Copying an element from a photo and pasting it into a painting is a challenging task. Applying photo compositing techniques in this context yields subpar results that look like a collage --- and existing painterly stylization algorithms, which are global, perform poorly when applied locally. We address these issues with a dedicated algorithm that carefully determines the local statistics to be transferred. We ensure both spatial and inter-scale statistical consistency and demonstrate that both aspects are key to generating quality results. To cope with the diversity of abstraction levels and types of paintings, we introduce a technique to adjust the parameters of the transfer depending on the painting. We show that our algorithm produces significantly better results than photo compositing or global stylization techniques and that it enables creative painterly edits that would be otherwise difficult to achieve.
Perhaps the best way to understand what the algorithm does is to look at a few sample images that it’s created.
The business would apply this type of algorithm and technology to serve as a branding, marketing, media, or social media company for individuals or businesses that are willing to pay for this type of unique imaging. For instance, I can image that a company like McDonalds might want to run a “rewriting history” campaign where something like this would be extremely interesting and useful.
While I’m not entirely sure what the business could or would do, the paper is interesting and I would encourage you to read it for yourself.
Monetization: Selling these images and/or licensing this technology
Contributed by: Michael Bervell (Billion Dollar Startup Ideas)