3 citations · 7 across the 4 of their papers we have counts for
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cs.CV2023★ 1 cited
Fake It Without Making It: Conditioned Face Generation for Accurate 3D Face Reconstruction
Will Rowan, Patrik Huber, Nick Pears +1
Accurate 3D face reconstruction from 2D images is an enabling technology with applications in healthcare, security, and creative industries. However, current state-of-the-art metho…
cs.CV2023★ 3 cited
Text2Face: A Multi-Modal 3D Face Model
Will Rowan, Patrik Huber, Nick Pears +1
We present the first 3D morphable modelling approach, whereby 3D face shape can be directly and completely defined using a textual prompt. Building on work in multi-modal learning,…
cs.CV2022★ 3 cited
The Effectiveness of Temporal Dependency in Deepfake Video Detection
Will Rowan, Nick Pears
Deepfakes are a form of synthetic image generation used to generate fake videos of individuals for malicious purposes. The resulting videos may be used to spread misinformation, re…