Less Redraw, More Explore: Suggestion and Completion for Sketch-to-Image

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Authors: Zeyu Zhao, C.J. van Rees, Gavin Bailey, Matt Jones, Simon Robinson, Jennifer S. Pearson
Cited by: 1
References: 36

Abstract

Sketch-to-image systems let users transform simple line drawings into realistic images, but current workflows force users into tedious redraw-regenerate cycles that slow creative exploration. We introduce two complementary interaction techniques that reduce iteration friction: AutoSketch, which extends partial sketches through AI-driven completions (pre-generation support), and BackSketch, which transforms generated images back into editable sketches at multiple abstraction levels (post-generation support). In a study with 30 participants, the results indicate that both techniques can improve exploration and expressiveness compared to a baseline sketch-to-image system, while AutoSketch also can increase users’ sense of agency and co-creation with the AI. We contribute new evidence that shifting support before or after generation opens distinct pathways for balancing user control and system initiative. Together, our results establish pre- and post-generation assistance as a design space for co-creative sketch-to-image systems.

Fields of Study & Subjects

Interactive and Immersive Displays Innovative Human-Technology Interaction Augmented Reality Applications

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–11
Publication date
13 April 2026
Language
EN