Generative AI in Product Photography: Human-Directed Transfer-Based Visual Workflows
This paper explores human-directed generative AI workflows for product photography, focusing on transfer-based visual methods that integrate real product photography with AI-generated environments. The study examines how reference images, prompt engineering, and iterative camera-angle synthesis enable controlled, brand-consistent visual outcomes while significantly reducing production costs and time. The proposed workflow positions AI as a collaborative tool rather than an autonomous creator, emphasizing the role of human artistic direction in concept development, aesthetic decision-making, and final image selection. Practical case studies demonstrate the applicability of these methods for commercial and creative product visualization.
Authors
- Oksana Bondarieva
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-01-22
- DOI
- https://doi.org/10.5281/zenodo.18343669
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00