88 citations · 184 across the 6 of their papers we have counts for
7 papers
A Perspective on Literary Metaphor in the Context of Generative AI
Imke van Heerden, Anil Bas
At the intersection of creative text generation and literary theory, this study explores the role of literary metaphor and its capacity to generate a range of meanings. In this reg…
AfriKI: Machine-in-the-Loop Afrikaans Poetry Generation
Imke van Heerden, Anil Bas
This paper proposes a generative language model called AfriKI. Our approach is based on an LSTM architecture trained on a small corpus of contemporary fiction. With the aim of prom…
Exploring Transformers in Natural Language Generation: GPT, BERT, and XLNet
M. Onat Topal, Anil Bas, Imke van Heerden
Recent years have seen a proliferation of attention mechanisms and the rise of Transformers in Natural Language Generation (NLG). Previously, state-of-the-art NLG architectures suc…
Statistical transformer networks: learning shape and appearance models via self supervision
Anil Bas, William A. P. Smith
We generalise Spatial Transformer Networks (STN) by replacing the parametric transformation of a fixed, regular sampling grid with a deformable, statistical shape model which is it…
3D Morphable Models as Spatial Transformer Networks
Anil Bas, Patrik Huber, William A. P. Smith +2
In this paper, we show how a 3D Morphable Model (i.e. a statistical model of the 3D shape of a class of objects such as faces) can be used to spatially transform input data as a mo…
What does 2D geometric information really tell us about 3D face shape?
Anil Bas, William A. P. Smith
A face image contains geometric cues in the form of configurational information and contours that can be used to estimate 3D face shape. While it is clear that 3D reconstruction fr…