A Design Space for Visual Interfaces for Generative Image Models

Abstract

Interactive visual interfaces have become an important means of controlling generative image models, enabling users to manipulate generation through prompts, direct manipulation, and a range of interactions. However, existing techniques are typically presented as independent systems, making it difficult to understand how they relate, compare their interaction mechanisms, or identify opportunities for new interface designs. We introduce a design space for interactive visual interfaces for generative image models derived from 51 research systems and practitioner tools. The framework decomposes each system into three complementary components: the user interface (U), the controllable model objects (Z), and the mapping function ($\phi$) that translates user interaction into model operations. This decomposition provides a common representation for analyzing heterogeneous interaction techniques across model families, revealing recurring design patterns and underexplored regions of the design space. We further present an interactive corpus explorer that support comparative analysis, and discuss usage scenarios for both educational settings and HCI/AI practitioners identifying research and design opportunities.