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TokenVerse: Multi-Concept Personalization in Token Modulation Space by Google (token-verse.github.io)
71 points by 037 10 hours ago | hide | past | favorite | 12 comments





Feels like a moodboarding multiplier for some design disciplines, if these aren't cherry-picked / transfer to other domains.

Pretty interesting.

Seems like you could apply similar ideas to text too.


This looks like an excellent step towards being able to apply consistency to generated images across a series.

It looks as if it would trivially integrate into Whisk, which already has a similar feature for defining an outputs “subjects” “scene” and “style”.

If it worked with people, they’d show people.

The second example in the "Results" section includes a human.

They do not show a realistic photo face transfer. They blur out the faces even.

It would be a huge invention, but they did not achieve that.


Below the first Results header is a carousel of images. If you tap the arrows you can explore — I believe there are three examples where the final image is a person who’s face was applied from a reference photo.

Yes. But. The reference photo is blurred. The smallest details matter for faces! That's the whole point. I have no doubt you can do a kind-of-looks-like faces. But this is the same issue since Dreambooth. All the IP transfer approaches, even the best like Ideogram's, are failing on faces.

There's two images where the face is transferred to the final image. The references images with blurred faces are all being used for a different reference; the pose, or "necklace", etc. The faces are blurred in every image unless they explicitly want the face transferred to the final image, at least that's how it seems.

I know. But there are no unblurred source images of faces. This isn't complicated.

https://token-verse.github.io/results/multi_concepts/25.png

https://token-verse.github.io/results/multi_concepts/06.png

Both of these show a man's face in a source image being used in a newly generated image. I agree that it isn't complicated, but you seem to be drawing different conclusions to everyone else here.

If your point is that it can't perform face transfer, you seem to be wrong - that's what's happening here. If your point is that the blurred photos used for other parts of the input mean that this suggests the model may get confused by other faces, then that's a fair point, but it seems clear they have demonstrated face transfer, and requiring blurring irrelevant faces seems a minor point compared to transferring the face that's intended. I'm not sure how that would really impact use-cases.


Well. It doesn't look like him. If they had working face / human character transfer, listen, my dude, every single image would show a face transfer. It's one of the biggest challenges.




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