[soulmerge]

Wow, I think this would be pretty useful as a shopping guide in an online shop: Let the user pick a few models they like and render more items based on the chosen ones. Present actual sneakers you have in stock at the last step.

[jstx1]

Maybe I'm not getting it. What's the benefit of showing people the imaginary sneakers? Why not show them what they can actually buy?

[soulmerge]

I think the experience is more like an employee coming to you and asking you what you're looking for in a shoe, instead of entering an empty store and browsing all available shoes. I would certainly prefer some guidance, as I usually have no clue what I'm looking for.

[klyrs]

(deep sarcasm)

Yeah, I love it when stores lure me in with products that I want, and then only have products that I don't want. I never rage-quit the store when that happens; I only ever buy dregs that they have in stock. I would love spending hours at a store browsing imaginary products that I can't buy; engagement is a perfect metric to predict profitability and the world needs a lot more than that.

All that said... if you change the contract a bit, it could work. Kinda like groupon, but people can browse AI-generated shoes and the most popular ones enter a tournament, and the winning design gets made for purchase. That could be pretty cool.

[StanvdVossen]

That's definitely a cool idea! I might ask around different webshops to see if they're interested in something like this.

[injidup]

Too many of those shoes look like they have a munged Nike logo which means that any company trying to ship them would soon be receiving a kindly call from the Nike megacorp lawyers. You would have to improve the training to avoid generating trademark / logo infringing designs. Could this be trivially done?

[StanvdVossen]

In general this would not be easy.

One way this can be accomplished is by removing all shoes with such logos from the training data. But Nike and Adidas are disproportionally large parts of my training set, so this would not be feasible.

The other option would be to train a machine learning model to recognize said logo's and to use this model to remove sneakers with logo's from my generated images. This could however greatly reduce the variety of images on the website.

[t_von_doom]

Slightly different implementation of your second option: Remove the logos in the dataset and train on this brand agnostic library

[t_von_doom]

EDIT: To clarify - don't remove the entire image of a sneaker, just impute away the logo filling in the space with the 'context fill' algorithm found in photo editing tools

[soulmerge]

I don't think that is an issue: The process should just help the user find the right shoe. If the user repeatedly picks shoes with a logo, he will be presented shoes of that brand, that the vendor has in stock. This is actually beneficial to the trademark holder.

[samwhiteUK]

Only real shoes would be shipped...