90 citations · 146 across the 11 of their papers we have counts for
12 papers
Robust Iris Centre Localisation for Assistive Eye-Gaze Tracking
Nipun Sandamal Ranasekara Pathiranage, Stefania Cristina, Kenneth P. Camilleri
In this research work, we address the problem of robust iris centre localisation in unconstrained conditions as a core component of our eye-gaze tracking platform. We investigate t…
The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks
Matthew Aquilina, Keith George Ciantar, Christian Galea +3
To date, the best-performing blind super-resolution (SR) techniques follow one of two paradigms: A) generate and train a standard SR network on synthetic low-resolution - high-reso…
State of the Art of Audio- and Video-Based Solutions for AAL
Slavisa Aleksic, Michael Atanasov, Jean Calleja Agius +36
The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) re…
Improving Super-Resolution Performance using Meta-Attention Layers
Matthew Aquilina, Christian Galea, John Abela +2
Convolutional Neural Networks (CNNs) have achieved impressive results across many super-resolution (SR) and image restoration tasks. While many such networks can upscale low-resolu…
On Architectures for Including Visual Information in Neural Language Models for Image Description
Marc Tanti, Albert Gatt, Kenneth P. Camilleri
A neural language model can be conditioned into generating descriptions for images by providing visual information apart from the sentence prefix. This visual information can be in…
Transfer learning from language models to image caption generators: Better models may not transfer better
Marc Tanti, Albert Gatt, Kenneth P. Camilleri
When designing a neural caption generator, a convolutional neural network can be used to extract image features. Is it possible to also use a neural language model to extract sente…
Quantifying the amount of visual information used by neural caption generators
Marc Tanti, Albert Gatt, Kenneth P. Camilleri
This paper addresses the sensitivity of neural image caption generators to their visual input. A sensitivity analysis and omission analysis based on image foils is reported, showin…
Pre-gen metrics: Predicting caption quality metrics without generating captions
Marc Tanti, Albert Gatt, Adrian Muscat
Image caption generation systems are typically evaluated against reference outputs. We show that it is possible to predict output quality without generating the captions, based on…
Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions
Albert Gatt, Marc Tanti, Adrian Muscat +6
The past few years have witnessed renewed interest in NLP tasks at the interface between vision and language. One intensively-studied problem is that of automatically generating te…
What is the Role of Recurrent Neural Networks (RNNs) in an Image Caption Generator?
Marc Tanti, Albert Gatt, Kenneth P. Camilleri
In neural image captioning systems, a recurrent neural network (RNN) is typically viewed as the primary `generation' component. This view suggests that the image features should be…
Where to put the Image in an Image Caption Generator
Marc Tanti, Albert Gatt, Kenneth P. Camilleri
When a recurrent neural network language model is used for caption generation, the image information can be fed to the neural network either by directly incorporating it in the RNN…
The Cyborg Astrobiologist: Porting from a wearable computer to the Astrobiology Phone-cam
Alexandra Bartolo, Patrick C. McGuire, Kenneth P. Camilleri +11
We have used a simple camera phone to significantly improve an `exploration system' for astrobiology and geology. This camera phone will make it much easier to develop and test com…