Felox/restore_skin

Hires Skin Texture · FLUX 3 Klein LoRA

A LoRA trained to restore high-pass skin detail lost to repeated VAE compression.

It works on the high-frequency layer only — pores, fine lines, peach fuzz, micro-specular — so it brings back texture without touching the color, lighting or composition of your image.

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Before / After

Close-up skin Pores and specular detail come back on the nose and under-eye area.	Portrait Wrinkles, stubble and skin grain recovered on a mid-shot.

Case 03 shows what the model actually works on: the isolated high-pass layer, before and after.

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Why this project?

Producing UGC-style renders means many back-and-forth rounds with clients — adding and removing elements from the frame. Every edit sends the image through another VAE encode/decode, whether you use local models or closed-source ones. Each pass destroys a little more of the fine detail, and after a few rounds the skin looks waxy and smoothed out.

This LoRA is the last step of that pipeline: it puts the texture back.

Training method

The dataset is built from high-quality skin texture images, which are then degraded by passing them through multiple VAEs. This reproduces the real-world damage of an iterative editing workflow.

Since we only want to train texture, we separate the high-pass detail of both the input (degraded) and the target (clean) images. The model learns to map a low-quality high-pass skin layer to a high-quality one.

Instead of a classic img2img workflow, this abstraction:

• keeps the model's attention on fine detail rather than on global content;
• avoids color shift in the outputs, because the low-frequency layer (color, tone, lighting) never goes through the model.

Base model	FLUX 3 Klein (black-forest-labs/flux-3-image-klein-base)
Type	LoRA
Input	High-pass layer of a VAE-degraded image
Target	High-pass layer of the clean source image
Degradation	Multiple VAE encode/decode passes
Rank / alpha	32
Steps / LR	2000
Resolution	2048

How to use

1. Split your image into a low-pass layer (Gaussian blur) and a high-pass layer
2. Run the high-pass layer through FLUX 3 Klein with this LoRA (image-to-image / edit). Trigger / prompt: Restore Skin, you can also use the given embeddings "restore_skin.safetensors".
3. Recombine the restored high-pass with the original low-pass.

4. A ComfyUI workflow is included: restore_skin_workflow.json

Why FLUX 3 Klein?

• Pixel-perfect output. The same training on FLUX 2 Klein (4B and 9B) produced pixel shift; FLUX 3 Klein stays aligned with the input, which is essential when the result is blended back onto the original.
• Best VAE for high-pass detail. The FLUX 2 VAE is, to date, the best available VAE for preserving high-frequency detail.

What about Bria 2?

Training started before Bria 2 was released, so it hasn't been tested. It could be explored, but its licensing seems more restrictive.

Limitations

• Trained on skin only — hair, fabric and backgrounds are not targeted and may receive limited or unwanted texture.
• Works best on images degraded by VAE round-trips; heavy JPEG blocking or strong motion blur are out of scope.

License

This LoRA is a derivative of FLUX 3 Klein and is distributed under the FLUX Kommunity License. Check the base model's terms before any commercial use.