Neural Networks for Adult Content: What They Can Do Today
The adult industry has traditionally adopted new technology ahead of everyone else — it did so with videotape, with paid access and with streaming. With AI the story repeats, but the tasks here differ and should not be conflated.
Four distinct tasks
- Generation from scratch — an image of an invented person from a text description
- Processing footage — working with real material: light, detail, retouching
- Face swapping — carrying one person's features onto video of another
- Enhancement — upscaling, restoring sharpness, raising frame rate
The first needs neither a model nor a shoot. The other three work with a real person, and that is where questions of consent arise.
What comes out well
Lighting and colour: confidently. Skin and textures: confidently. Composition and pose: with reservations. Upscaling old material: very well indeed, and this is one of the most underrated applications — a decade-old archive can be brought to modern resolution.
What comes out badly
Anything requiring an understanding of physics and anatomy in motion: interaction between two or more figures, long hair moving, fabric, reflections. The more objects interact in a frame, the faster the model loses coherence.
On the pace of change
The list of things that «do not work» shrinks every few months. It is wiser to orient not by specific limitations but by the principle: a model is good where training data was plentiful and weak where it was scarce. An unusual angle, an unusual pose, an unusual appearance — always harder.
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