Learning to See: You Are What You See
February 28, 2020 Β· Declared Dead Β· π ACM SIGGRAPH 2019 Art Gallery
"No code URL or promise found in abstract"
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Authors
Memo Akten, Rebecca Fiebrink, Mick Grierson
arXiv ID
2003.00902
Category
cs.CV: Computer Vision
Cross-listed
cs.GR,
cs.HC,
cs.LG
Citations
28
Venue
ACM SIGGRAPH 2019 Art Gallery
Last Checked
5 months ago
Abstract
The authors present a visual instrument developed as part of the creation of the artwork Learning to See. The artwork explores bias in artificial neural networks and provides mechanisms for the manipulation of specifically trained for real-world representations. The exploration of these representations acts as a metaphor for the process of developing a visual understanding and/or visual vocabulary of the world. These representations can be explored and manipulated in real time, and have been produced in such a way so as to reflect specific creative perspectives that call into question the relationship between how both artificial neural networks and humans may construct meaning.
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