Růžička, Vít (2021) Latent Rider. [Art/Design Item]
![[img]](https://ualresearchonline.arts.ac.uk/style/images/fileicons/video.png)
| Type of Research: | Art/Design Item | ||||||
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| Creators: | Růžička, Vít | ||||||
| Description: | We are participants in systems larger than us, single organisms moving inside systems of cities or processed samples of data in the overarching flow of information through neural networks. Step forward into the accelerating bus of reinterpreted and generated reality. This is an experimental short film which explores the latent space of generative models trained on my own collected and curated selections of scenes. The concept of film editing is replaced by escalating jumps in the latent space, montage of feature vectors and sequences based on similarity rather than time. Imagery is reinterpreted and reordered following a compressed form. |
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| Keywords/subjects not otherwise listed: | Generative Neural Networks | ||||||
| Your affiliations with UAL: | Research Centres/Networks > Institute for Creative Computing | ||||||
| Date: | May 2021 | ||||||
| Related Websites: | https://computervisionart.com/pieces2021/latent-rider/, https://github.com/ual-cci/GAN_explorer | ||||||
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| Related Exhibitions: | CVPR, Computer Vision Art Gallery, 2021 | ||||||
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| Material/Media: | Neural Network generated footage, my own video as data | ||||||
| Measurements or Duration of item: | 2:34 min | ||||||
| Date Deposited: | 28 Apr 2022 15:41 | ||||||
| Last Modified: | 28 Apr 2022 15:41 | ||||||
| Item ID: | 18099 | ||||||
| URI: | https://ualresearchonline.arts.ac.uk/id/eprint/18099 |
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