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20172020
most citedPlane-extraction from depth-data using a Gaussian mixture regression model

14 citations · 23 across the 5 of their papers we have counts for

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cs.CV2020★ 1 cited

An Assessment of GANs for Identity-related Applications

Richard T. Marriott, Safa Madiouni, Sami Romdhani +2

Generative Adversarial Networks (GANs) are now capable of producing synthetic face images of exceptionally high visual quality. In parallel to the development of GANs themselves, e…

cs.CV2020★ 1 cited

Robustness of Facial Recognition to GAN-based Face-morphing Attacks

Richard T. Marriott, Sami Romdhani, Stéphane Gentric +1

Face-morphing attacks have been a cause for concern for a number of years. Striving to remain one step ahead of attackers, researchers have proposed many methods of both creating a…

cs.CV2020★ 3 cited

A 3D GAN for Improved Large-pose Facial Recognition

Richard T. Marriott, Sami Romdhani, Liming Chen

Facial recognition using deep convolutional neural networks relies on the availability of large datasets of face images. Many examples of identities are needed, and for each identi…

cs.CV2018★ 4 cited

Taking Control of Intra-class Variation in Conditional GANs Under Weak Supervision

Richard T. Marriott, Sami Romdhani, Liming Chen

Generative Adversarial Networks (GANs) are able to learn mappings between simple, relatively low-dimensional, random distributions and points on the manifold of realistic images in…

cs.CV2017★ 14 cited

Plane-extraction from depth-data using a Gaussian mixture regression model

Richard T. Marriott, Alexander Paschevich, Radu Horaud

We propose a novel algorithm for unsupervised extraction of piecewise planar models from depth-data. Among other applications, such models are a good way of enabling autonomous age…