Generating a new image using an existing image as input alongside a text prompt. The input image anchors composition, pose or subject while the prompt steers what changes.
Where text-to-image starts from nothing, image-to-image starts from a picture: the input provides structure — composition, pose, subject placement — and the prompt plus a strength setting decide how far the output may depart from it. Low strength refines; high strength reinvents within the same bones.
Typical uses in persona work: restyling a good shot into a different mood, changing wardrobe or setting while keeping a pose, adapting one hero image into placement variants, and product-focused edits where the composition is already right. Garment-focused workflows like virtual try-on are specialized forms of the same idea.
It is worth keeping the conceptual line clear: image-to-image is per-image guidance — it borrows from one specific picture, once. Model training is persistent identity — the persona exists independent of any single source image. The two combine well: train the identity, then use image-to-image to iterate on individual results.
Related terms
Generating an image purely from a written description. The model synthesizes composition, subject, lighting and style from the prompt alone, with no input image.
Increasing an image's pixel resolution, typically with an AI model that synthesizes plausible fine detail. Distinct from rendering at a high resolution natively.
Generating images of a specific garment or product being worn by a model without a physical photoshoot. Used in fashion e-commerce to show items on-body across looks, scenes and variants.