Artistic control over the glitch in AI-generated motion capture
August 16, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Jamal Knight, Andrew Johnston, Adam Berry
arXiv ID
2308.08576
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.GR
Citations
3
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Artificial intelligence (AI) models are prevalent today and provide a valuable tool for artists. However, a lesser-known artifact that comes with AI models that is not always discussed is the glitch. Glitches occur for various reasons; sometimes, they are known, and sometimes they are a mystery. Artists who use AI models to generate art might not understand the reason for the glitch but often want to experiment and explore novel ways of augmenting the output of the glitch. This paper discusses some of the questions artists have when leveraging the glitch in AI art production. It explores the unexpected positive outcomes produced by glitches in the specific context of motion capture and performance art.
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