Traditionally, 3D artists had three ways to create textures:
- Photography and processing: Find a suitable surface, photograph it in the right light, and then spend hours in Photoshop or another editor removing glare and shadows and making it seamless (tailored).
- Manual drawing: Use programs like Substance Painter or 3DCoat to draw textures directly onto the model. Requires advanced artistic skills.
- Procedural generation: Create complex graphs from nodes in Substance Designer to generate materials. Powerful, but has a very high entry threshold and requires an analytical mindset.
All of these methods are effective, but require either time or highly specialized skills. AI generators based on diffuse models offer a fourth, revolutionary path.
How does it work (in simple terms)? Imagine showing a neural network millions of photos of wood in all its forms: boards, bark, saw cuts, polished furniture. Then you “noise up” these images, gradually turning them into a chaotic set of pixels. The neural network learns to do the reverse process: from pure noise, guided by a text description (“old pine board with peeling paint”), it step by step “develops” an image that matches the request. And since it was trained on PBR data, it can “develop” not just one image, but a whole set of maps at once, understanding how color, roughness, and relief are related for a given material.
Key advantages of AI in texturing:
- Speed: Generating a complete set of PBR maps in 4K resolution can take anywhere from a few seconds to a couple of minutes. This is orders of magnitude faster than traditional methods.
- Endless variations: Do you need not just a “brick texture,” but “old Victorian-era fired brick with moss stains and salt deposits”? Just describe it. You can generate dozens of unique variations in minutes and choose the best one.
- Lower entry threshold: Artists no longer need to be experts in procedural generation or Photoshop masters. The main skill becomes prompt engineering—the ability to accurately and vividly describe the desired result.
- Creative catalyst: AI can generate concepts and options that you may not have considered. It becomes not just an executor, but a creative partner that contributes ideas.
Of course, it is not a magic button that will automatically produce beautiful results. The quality of the outcome directly depends on the quality of the AI model and your ability to manage it.