The context of new media art for photography generation based on diffusion models
Chenye Zhang · 2026
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Description
Chenye Zhang proposes a control system for AI-generated photography aimed at new media artists, in a 2026 study of diffusion models. Plain text prompts give artists too little say over meaning, composition, and style. The framework layers three kinds of control onto a latent diffusion model. Semantic guidance comes from a vision and language model. Spatial layout mapping supplies structure, and style loss tuning sets the look. Attention and consistency mechanisms hold the image together.
On standard quality scores the system beat a popular baseline model, posting better realism and text-matching numbers. Removing the layout module hurt quality scores, and removing style control visibly reduced realism, confirming both parts carry weight. Zhang offers the framework as a technical path toward generated photographs that carry deliberate artistic and narrative intent.
Catalog record
| CREATOR | Chenye Zhang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 56973 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |