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GANSlider : How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information

Title data

Dang, Hai ; Mecke, Lukas ; Buschek, Daniel:
GANSlider : How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information.
2022
Event: CHI Conference on Human Factors in Computing Systems , 30.04. - 06.05.2022 , New Orleans, LA, USA.
(Conference item: Conference , Paper )
DOI: https://doi.org/10.1145/3491102.3502141

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Project's official titleProject's id
AI Tools - Continuous Interaction with Computational Intelligence ToolsNo information

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https://osf.io/tze2x/

Abstract in another language

We investigate how multiple sliders with and without feedforward visualizations influence users' control of generative models. In an online study (N=138), we collected a dataset of people interacting with a generative adversarial network (StyleGAN2) in an image reconstruction task. We found that more control dimensions (sliders) significantly increase task difficulty and user actions. Visual feedforward partly mitigates this by enabling more goal-directed interaction. However, we found no evidence of faster or more accurate task performance. This indicates a tradeoff between feedforward detail and implied cognitive costs, such as attention. Moreover, we found that visualizations alone are not always sufficient for users to understand individual control dimensions. Our study quantifies fundamental UI design factors and resulting interaction behavior in this context, revealing opportunities for improvement in the UI design for interactive applications of generative models. We close by discussing design directions and further aspects.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: interactive AI; generative adversarial network; image manipulation; user study; dataset
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 09 Feb 2022 07:56
Last Modified: 11 Feb 2022 11:18
URI: https://eref.uni-bayreuth.de/id/eprint/68584