Trinketry: Tracing and Recombining Visual Elements in Generative Design Exploration

Abstract

Generative AI systems allow visual designers to rapidly produce many image alternatives, but preserving, revisiting, and building on promising partial results across iterations remains challenging. In practice, generated images are rarely valuable as complete wholes; instead, designers often reuse fragments, revisit earlier materials, and combine partial ideas into new directions. We present Trinketry, an element-centered visual exploration system built around trinkets: reusable visual and semantic elements extracted from prior generations. Trinketry allows users to extract image regions, whole images, text labels, and composite elements; recombine them in intention trays to generate new variations; trace the provenance of specific elements across the exploration process; and retrieve semantically related prior outcomes. By foregrounding extraction, recombination, tracing, and retrieval, this demo presents an alternative interaction model for AI-assisted visual exploration—one that supports traceable reuse, intentional iteration, and reflective design exploration.