5 ms·

Because it’s trained on “real” people, will it be easier to generate ugly people? I have a hard time convincing DALL-E to give me ugly DnD character portraits.

wobbly_bush 3y ago
Aren't Insta images heavily edited?
- rchaud 3y ago
  Yes, with filters supplied by Instagram, so they would still have the original camera images.
doctorpangloss 3y ago
> Because it’s trained on “real” people, will it be easier to generate ugly people? In the literature, testing concepts in image generation is asking human graders "which image do you prefer more for this caption?," so the answer is probably no. You could speculate on all the approaches that would help this system learn the concept "ugly," and they would probably work, but it would be hard to measure.
PUSH_AX 3y ago
In order for a model to understand what ugly is, someone or something has to tag training data as “ugly”, I find this to be a complete can of worms
- Jerrrry 3y ago
  >In order for a model to understand what ugly is, someone or something has to tag training data as “ugly”, that is a very dated (2008) concept. the model "understands" that 50% of people are below/above median. consequently, those that are not "OMG girl ur BEAUTIFUL"-tagged are horse-faced. It understands that the girl with the profile picture with 200 likes and 2k friends is better looking than the girl with 4 likes and 500 friends.
  - PUSH_AX 3y ago
    I fine tuned some checkpoints this year (2023), and that's exactly how it worked. Unless your model is single focus for humans and faces I find it hard to believe there is specific business logic in the training process around inferring beauty from social engagement. Metas model is general purpose.
  - squigz 3y ago
    > It understands that the girl with the profile picture with 200 likes and 2k friends is better looking than the girl with 4 likes and 500 friends. I'm not very familiar with model training. How does it understand this? Is such information part of the training data?
- Guillaume86 3y ago
  Put beautiful/pretty in the negative prompt, should get a similar result without the need for tagging ugly in the training set.
hbossy 3y ago
Try asking for asymmetry. The more images of faces you average, the better they look.

wobbly_bush 3y ago

Aren't Insta images heavily edited?

rchaud 3y ago
Yes, with filters supplied by Instagram, so they would still have the original camera images.

doctorpangloss 3y ago

> Because it’s trained on “real” people, will it be easier to generate ugly people? In the literature, testing concepts in image generation is asking human graders "which image do you prefer more for this caption?," so the answer is probably no. You could speculate on all the approaches that would help this system learn the concept "ugly," and they would probably work, but it would be hard to measure.

PUSH_AX 3y ago

In order for a model to understand what ugly is, someone or something has to tag training data as “ugly”, I find this to be a complete can of worms

Jerrrry 3y ago
>In order for a model to understand what ugly is, someone or something has to tag training data as “ugly”, that is a very dated (2008) concept. the model "understands" that 50% of people are below/above median. consequently, those that are not "OMG girl ur BEAUTIFUL"-tagged are horse-faced. It understands that the girl with the profile picture with 200 likes and 2k friends is better looking than the girl with 4 likes and 500 friends.
- PUSH_AX 3y ago
  I fine tuned some checkpoints this year (2023), and that's exactly how it worked. Unless your model is single focus for humans and faces I find it hard to believe there is specific business logic in the training process around inferring beauty from social engagement. Metas model is general purpose.
- squigz 3y ago
  > It understands that the girl with the profile picture with 200 likes and 2k friends is better looking than the girl with 4 likes and 500 friends. I'm not very familiar with model training. How does it understand this? Is such information part of the training data?
Guillaume86 3y ago
Put beautiful/pretty in the negative prompt, should get a similar result without the need for tagging ugly in the training set.

hbossy 3y ago

Try asking for asymmetry. The more images of faces you average, the better they look.