DeckFlow: A Card Game Interface for Exploring Generative Model Flows

Gregory Thomas Croisdale, John Joon Young Chung, Emily Huang, Gage Birchmeier, Xu Wang, Anhong Guo

Abstract: Recent Generative AI models have been shown to be substantially useful in different fields, often bridging modal gaps, such as text-prompted image or human motion generation. However, their accompanying interfaces do not sufficiently support iteration and interaction between models, and due to the computational intensity of generative technology, can be unforgiving to user errors and missteps. We propose DeckFlow, a no-code interface for multimodal generative workflows which encourages rapid iteration and experimentation between disparate models. DeckFlow emphasizes the persistence of output, the maintenance of generation settings and dependencies, and continual steering through user-defined concept groups. Taking design cues from Card Games and Affinity Diagrams, DeckFlow is aimed to lower the barrier for non-experts to explore and interact with generative AI.