Personal Project · AI Imagery · Character LoRA · Digital Twin
One man, fourteen eras, one denim shirt.
Ken travels through time – from a pirate ship off Cape Horn to the Wild West, from the Jurassic to the summit of Everest – always in the same denim shirt, always with his iPhone in hand.
There are many ways to bring a real person into AI images today. Training a LoRA used to be one of the few reliable ones – and it has gone a little out of fashion, mainly because training one takes real effort.
Done well, it delivers a realism and consistency that a handful of reference images cannot match: the model gets to know a person far more thoroughly. In our view, it comes close to beating a hybrid production with a real shoot.
Whichever route you take, in the end it is the post team that brings it home.
Hamburg model agency Procast provided a dataset of their model Ken. With it, we trained our own LoRA and sent Ken on a journey through fourteen eras – reacting to each world, shooting it on his phone, and always staying himself.
Insights
LoRAs have their downsides: the model often learns parts of the training backgrounds too, and a LoRA that is too strong limits the creative range of the base model. Finding the right training parameters and weighting is a fine balance.
01
240 portraits of Ken: one person, one outfit, five lighting setups – studio, brick wall in hard sun, street in daylight.
02
73 images chosen to cover every angle, every light and every framing from close-up to full figure – near-duplicates out, so no pose gets over-weighted.
03
Each image gets a caption with a trigger word. Whatever may change – clothing, background, light, pose – is described. What makes Ken Ken is deliberately left out.
04
A character LoRA on Qwen-Image 2.1, trained locally with AI Toolkit and tested checkpoint by checkpoint. Step 2000 at a strength of 0.9 proved the best balance; FLUX.3 was tested in parallel.
05
Short prompts, film look first. Each era rendered with ten seeds – over 400 renderings across 23 scenes, from which the final series was curated.
06
Extras began to take on Ken's face. Every face in every image was measured automatically; look-alikes were repainted without the LoRA, aware of gender and expression.
07
A SeedVR2 upscale on the ungraded images, then one consistent analog grade: S-curve, lifted blacks, split tone, vignette and grain scaled to the image size.














Everything was produced locally, in our own ComfyUI pipeline – from the LoRA training to the automatic face check and the final grade.
AI Imaging: Robert Brembeck · Model: Ken, Procast Hamburg