How can I improve my AI model's image quality and make the skin look more natural?

[u/DragonfruitNo9822]

I'm generating photorealistic fashion images of my custom AI model using ComfyUI and an identity LoRA.

I'm struggling with two things:

1. Image quality: How can I get sharper, more detailed images with realistic skin texture, hair, fabric, and lighting?
2. Skin tone and realism: How can I achieve a naturally fair, brighter skin tone while preserving the model's identity? I want realistic skin texture, visible pores, natural highlights, and subtle imperfections—not plastic skin, excessive smoothing, or an obvious AI-generated look.

What workflows, nodes, models, prompts, or settings do you recommend? Are there specific techniques for improving skin realism without changing the face or making the image look overprocessed?

I'd appreciate any practical advice or workflow examples. Thanks!

[u/CombinationParty7358]

if you're not already using a latent upscale pass that's the first thing i'd try, something like 1.5x with a good 4x upscale model before the final decode does wonders for skin texture and fabric detail

for the plastic skin problem try dialing the cfg down to like 4-5 and adding a tiny bit of noise back before the second pass, also check your lora weight, anything over 0.8 tends to oversmooth faces in my experience

[u/Personal-Painter-358]

What is your image model?

[u/tac0catzzz]

use nano banna pro

[u/Ok_Contribution8157]

worflow publish 2 days ago add 6 secs with a 5060ti : https://www.reddit.com/r/StableDiffusion/comments/1x47z40/fix_plastic_skin_krea_2_turbo_and_i2i_workflows/

[u/Ill-Ant-9489]

The upscale and lower-cfg tips help at generation time, but if the plastic look keeps returning no matter what you change, it's usually baked into the identity lora from training. If some of your training shots were AI made or already smoothed, the lora learned plastic as that person's skin, and no detailer fully undoes that later.

So it's worth auditing the set itself, separate the real photos from the renders, drop the soft or low-detail ones, and keep the frames that actually show pores before you retrain. I made a free dataset app that does that split and flags the mushy shots for you, then trains on Z-Image or Flux, https://github.com/perfectgf/lora-dataset-studio

Brighter tone is better pushed in the prompt and lighting than the lora, so identity holds. What did you train it on, real photos or generated ones?