Conference Paper/Proceeding/Abstract 551 views 15 downloads
Less Redraw, More Explore: Suggestion and Completion for Sketch-to-Image
,
Connor Rees,
Gavin Bailey ,
Matt Jones ,
Simon Robinson ,
Jen Pearson
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, Pages: 1 - 11
Swansea University Authors:
Zeyu Zhao , Connor Rees, Gavin Bailey , Matt Jones , Simon Robinson , Jen Pearson
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DOI (Published version): 10.1145/3772318.3791026
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 exte...
| Published in: | Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems |
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| ISBN: | 979-8-4007-2278-3 |
| Published: |
New York, NY, USA
Association for Computing Machinery (ACM)
2026
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71270 |
| 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. |
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| Keywords: |
Generative AI, sketch-to-image, creativity, user interface, image generation, user study |
| College: |
Faculty of Science and Engineering |
| Funders: |
This work was supported by Engineering and Physical Sciences Research Council grant EP/Y010477/1. |
| Start Page: |
1 |
| End Page: |
11 |