1 citations · 3 across the 4 of their papers we have counts for
6 papers
Face2Text revisited: Improved data set and baseline results
Marc Tanti, Shaun Abdilla, Adrian Muscat +3
Current image description generation models do not transfer well to the task of describing human faces. To encourage the development of more human-focused descriptions, we develope…
Predicting Relative Depth between Objects from Semantic Features
Stefan Cassar, Adrian Muscat, Dylan Seychell
Vision and language tasks such as Visual Relation Detection and Visual Question Answering benefit from semantic features that afford proper grounding of language. The 3D depth of o…
One vs Previous and Similar Classes Learning -- A Comparative Study
Daniel Cauchi, Adrian Muscat
When dealing with multi-class classification problems, it is common practice to build a model consisting of a series of binary classifiers using a learning paradigm which dictates…
VJAGG -- A Thick-Client Smart-Phone Journey Detection Algorithm
Michael P. J. Camilleri, Adrian Muscat, Victor Buttigieg +1
In this paper we describe , a battery-aware journey detection algorithm that executes on the mobile device. The algorithm can be embedded in the client app of th…
Optimising the Input Image to Improve Visual Relationship Detection
Noel Mizzi, Adrian Muscat
Visual Relationship Detection is defined as, given an image composed of a subject and an object, the correct relation is predicted. To improve the visual part of this difficult pro…
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…