Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Baş, Anıl"'
Autor:
van Heerden, Imke, Bas, Anil
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 regard, literary metaphor is vital to the development of any particular l
Externí odkaz:
http://arxiv.org/abs/2409.01053
Autor:
van Heerden, Imke, Bas, Anil
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 promoting human creativity, we use the model as an authoring tool to explo
Externí odkaz:
http://arxiv.org/abs/2103.16190
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 such as RNN and LSTM ran into vanishing gradient problems; as sentences g
Externí odkaz:
http://arxiv.org/abs/2102.08036
Autor:
Bas, Anil, Smith, William A. P.
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 itself learnt. We call this a Statistical Transformer Network (StaTN). B
Externí odkaz:
http://arxiv.org/abs/1804.02541
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 module (a 3DMM-STN) within a convolutional neural network. This is an ex
Externí odkaz:
http://arxiv.org/abs/1708.07199
Autor:
Bas, Anil, Smith, William A. P.
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 from 2D points is highly ambiguous if no further constraints are enforce
Externí odkaz:
http://arxiv.org/abs/1708.06703
We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based
Externí odkaz:
http://arxiv.org/abs/1602.01125
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