Projects per year
The automated evaluation of creative products promises both good-and-scalable creativity assessments and new forms of visual analysis of whole corpora. Where creative works are not ‘born digital’, such automated evaluation requires fast and frugal ways of transforming them into data representations that can be meaningfully assessed with common creativity metrics like novelty. In this paper, we report the results of training a Spatiotemporal DeepInfomax Variational Autoencoder (STDIM-VAE) on a digital photo pool of 162 LEGO ducks to generate a phenotypical landscape of clusters of similar ducks and dissimilarity scores for individual ducks. Visual inspection suggests that our system produces plausible results from image pixels alone. We conclude that under certain conditions, STDIM-VAEs may provide fast and frugal ways of automatically assessing corpora of creative works.
|Title of host publication||ICCC'20: Eleventh International Conference on Computational Creativity|
|Publisher||Association for Computational Creativity (ACC)|
|Number of pages||4|
|Publication status||Accepted/In press - 30 Jun 2020|
EPSRC IGGI CDT
Cairns, P. A. & Cowling, P. I.
1/04/14 → 31/10/24
Project: Research project (funded) › Studentship (central)
The Digital Creativity Hub
Cowling, P. I., Austin, J., Cairns, P. A., Holliman, N. S., Hook, J. D., Marsden, E., Murphy, D. T., Petrie, H., Reed, D. J., Richards, J. D., Ursu, M., Wade, A., Baier, H., Beale, G., Block, F. O., Deterding, C. S., Devlin, S., Drachen, A., Kasprowicz, R. E., Smith, D. P. & Williams, D. A. H.
1/10/15 → 30/09/22
Project: Research project (funded) › Research