u/Enough-Bell4944

The internet is full of normal, candid photos of people with natural skin texture. Theres a subset of heavily retouched editorial or beauty photography with that smooth porcelain skin look, but that’s clearly a minority of all human images online. Most photos of people are just regular snapshots where skin looks like actual skin.

So why do image models, especially open source ones, struggle so much to generate realistic looking people out of the box? Why do they default to this plasticky, airbrushed, over-retouched aesthetic when that’s not what the majority of the training data actually looks like?

Its striking how hard it is for models to reproduce something as common and statistically ordinary as normal human skin without needing specialized prompting, LoRAs, finetunes, or upscalers. Natural skin texture should arguably be the baseline behavior, yet it very obviously isnt. Why?

I recently asked why porn finetunes are still so far behind general purpose imagegen models. The answers I got made sense: major companies avoid this space because of legal and reputational risks, while the open source community struggles because building a truly competitive model would be extremely expensive.

But realistically, when do you think goon image models will reach the same level of realism, coherence, and flexibility as something like Nano Banana Pro?

People have recommended Chroma and various SDXL checkpoints from Civitai, but none of them really come close. They often look like CGI, or at best like heavily retouched Playboy images from the mid 2000s. They also lack the broader world knowledge, prompt understanding, anatomical consistency and overall coherence that models like ChatGPTs imagegen or Nano Banana Pro seem to have.

One possible path would be to use a strong frontier model to generate a large synthetic dataset, maybe tens of thousands of images, then train an open source model on that to distill some of its knowledge around anatomy, lighting, poses, composition, and general visual coherence and realism. After that, the model could be further finetuned on a smaller but well labeled porn dataset.

The problem is that this would require a serious amount of money, technical skill and curation, so it is not surprising that nobody has really done it properly yet. Maybe this is the kind of thing that would need a serious crowdfunding effort or a dedicated community project.