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Rapid tracking of extrinsic projector parameters in fringe projection using machine learning (2018)
Journal Article
Stavroulakis, P., Chen, S., Delorme, C., Bointon, P., Tzimiropoulos, G., & Leach, R. (2019). Rapid tracking of extrinsic projector parameters in fringe projection using machine learning. Optics and Lasers in Engineering, 114, 7-14. https://doi.org/10.1016/j.optlaseng.2018.08.018

In this work, we propose to enable the angular re-orientation of a projector within a fringe projection system in real-time without the need for re-calibrating the system. The estimation of the extrinsic orientation parameters of the projector is per... Read More about Rapid tracking of extrinsic projector parameters in fringe projection using machine learning.

Zero-Shot Keyword Spotting for Visual Speech Recognition In-the-wild (2018)
Conference Proceeding
Tzimiropoulos, Y., & Stafylakis, T. (2018). Zero-Shot Keyword Spotting for Visual Speech Recognition In-the-wild. In Computer Vision – ECCV 2018 (536-552). https://doi.org/10.1007/978-3-030-01225-0_32

Visual keyword spotting (KWS) is the problem of estimating whether a text query occurs in a given recording using only video information. This paper focuses on visual KWS for words unseen during training, a real-world, practical setting which so far... Read More about Zero-Shot Keyword Spotting for Visual Speech Recognition In-the-wild.

To Learn Image Super-Resolution, Use a GAN to Learn How to Do Image Degradation First (2018)
Conference Proceeding
Bulat, A., Yang, J., & Tzimiropoulos, G. (2018). To Learn Image Super-Resolution, Use a GAN to Learn How to Do Image Degradation First. In Computer Vision – ECCV 2018: 15th European Conference Munich, Germany, September 8–14, 2018 Proceedings, Part VI (187-202). https://doi.org/10.1007/978-3-030-01231-1_12

© Springer Nature Switzerland AG 2018. This paper is on image and face super-resolution. The vast majority of prior work for this problem focus on how to increase the resolution of low-resolution images which are artificially generated by simple bili... Read More about To Learn Image Super-Resolution, Use a GAN to Learn How to Do Image Degradation First.

Hierarchical binary CNNs for landmark localization with limited resources (2018)
Journal Article
Bulat, A., & Tzimiropoulos, G. (2020). Hierarchical binary CNNs for landmark localization with limited resources. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(2), 343 - 356. https://doi.org/10.1109/tpami.2018.2866051

Our goal is to design architectures that retain the groundbreaking performance of Convolutional Neural Networks (CNNs) for landmark localization and at the same time are lightweight, compact and suitable for applications with limited computational re... Read More about Hierarchical binary CNNs for landmark localization with limited resources.

Novel monitoring systems to obtain dairy cattle phenotypes associated with sustainable production (2018)
Journal Article
Bell, M. J., & Tzimiropoulos, G. (2018). Novel monitoring systems to obtain dairy cattle phenotypes associated with sustainable production. Frontiers in Sustainable Food Systems, 2, Article 31. https://doi.org/10.3389/fsufs.2018.00031

Improvements in production efficiencies and profitability of products from cattle are of great interest to farmers. Furthermore, improvements in production efficiencies associated with feed utilization and fitness traits have also been shown to reduc... Read More about Novel monitoring systems to obtain dairy cattle phenotypes associated with sustainable production.

End-to-end audiovisual speech recognition (2018)
Conference Proceeding
Petridis, S., Stafylakis, T., Ma, P., Cai, F., Tzimiropoulos, G., & Pantic, M. (2018). End-to-end audiovisual speech recognition.

Several end-to-end deep learning approaches have been recently presented which extract either audio or visual features from the input images or audio signals and perform speech recognition. However, research on end-to-end audiovisual models is very l... Read More about End-to-end audiovisual speech recognition.