1 code implementation • 8 Mar 2023 • Anwesha Mohanty, Alistair Sutherland, Marija Bezbradica, Hossein Javidnia
In this study, for the first time, a small dataset of Rosacea with 300 full-face images is utilized to further investigate the possibility of generating synthetic data.
no code implementations • 26 Jun 2020 • Ivan Bacher, Hossein Javidnia, Soumyabrata Dev, Rahul Agrahari, Murhaf Hossari, Matthew Nicholson, Clare Conran, Jian Tang, Peng Song, David Corrigan, François Pitié
Over the past decade, the evolution of video-sharing platforms has attracted a significant amount of investments on contextual advertising.
no code implementations • 21 Jun 2020 • Shubhajit Basak, Hossein Javidnia, Faisal Khan, Rachel McDonnell, Michael Schukat
Creating a dataset that represents all variations of real-world faces is not feasible as the control over the quality of the data decreases with the size of the dataset.
no code implementations • 11 Feb 2020 • Hossein Javidnia, François Pitié
The current state of the art alpha matting methods mainly rely on the trimap as the secondary and only guidance to estimate alpha.
no code implementations • 8 Oct 2019 • Soumyabrata Dev, Hossein Javidnia, Murhaf Hossari, Matthew Nicholson, Killian McCabe, Atul Nautiyal, Clare Conran, Jian Tang, Wei Xu, François Pitié
Virtual advertising is an important and promising feature in the area of online advertising.
no code implementations • 1 May 2018 • Shabab Bazrafkan, Hossein Javidnia, Peter Corcoran
One of the most interesting challenges in Artificial Intelligence is to train conditional generators which are able to provide labeled adversarial samples drawn from a specific distribution.
no code implementations • 1 Feb 2018 • Shabab Bazrafkan, Hossein Javidnia, Peter Corcoran
There have been a tremendous amount of attempts to detect these points from facial images however, there has never been an attempt to synthesize a random face and generate its corresponding facial landmarks.
Image and Video Processing
no code implementations • 21 Nov 2017 • Hossein Javidnia, Peter Corcoran
To tackle this issue, in this paper, a framework is proposed based on Preconditioned Alternating Direction Method of Multipliers (PADMM) for depth from the focal stack and synthetic defocus application.
no code implementations • 21 Nov 2017 • Hossein Javidnia, Peter Corcoran
Evaluation of this method based on a well-known benchmark indicates that the proposed framework performs well in terms of accuracy when compared to the top-ranked depth estimation methods and a baseline algorithm.