27 citations · 58 across the 7 of their papers we have counts for
5 papers · 1 filter
Network Bending: Expressive Manipulation of Deep Generative Models
Terence Broad, Frederic Fol Leymarie, Mick Grierson
We introduce a new framework for manipulating and interacting with deep generative models that we call network bending. We present a comprehensive set of deterministic transformati…
Learning to See: You Are What You See
Memo Akten, Rebecca Fiebrink, Mick Grierson
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 mecha…
Deep Meditations: Controlled navigation of latent space
Memo Akten, Rebecca Fiebrink, Mick Grierson
We introduce a method which allows users to creatively explore and navigate the vast latent spaces of deep generative models. Specifically, our method enables users to \textit{disc…
Amplifying The Uncanny
Terence Broad, Frederic Fol Leymarie, Mick Grierson
Deep neural networks have become remarkably good at producing realistic deepfakes, images of people that (to the untrained eye) are indistinguishable from real images. Deepfakes ar…
Calligraphic Stylisation Learning with a Physiologically Plausible Model of Movement and Recurrent Neural Networks
Daniel Berio, Memo Akten, Frederic Fol Leymarie +2
We propose a computational framework to learn stylisation patterns from example drawings or writings, and then generate new trajectories that possess similar stylistic qualities. W…