12 citations · 13 across the 5 of their papers we have counts for
5 papers
MAP: A Benchmark on Multimodal Accessibility Planning for Real World Places
Jason Armitage, Ioannis Tsochantaridis, Linda Mazzone +3
We introduce MAP, the first benchmark to evaluate multimodal AI systems as assistants for users with accessibility requirements when planning visits to places in the real world. In…
Video and Language Alignment in 2D Systems for 3D Multi-object Scenes with Multi-Information Derivative-Free Control
Jason Armitage, Rico Sennnrich
Cross-modal systems trained on 2D visual inputs are presented with a dimensional shift when processing 3D scenes. An in-scene camera bridges the dimensionality gap but requires lea…
A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues
Jason Armitage, Leonardo Impett, Rico Sennrich
In a busy city street, a pedestrian surrounded by distractions can pick out a single sign if it is relevant to their route. Artificial agents in outdoor Vision-and-Language Navigat…
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and Modalities
Jason Armitage, Endri Kacupaj, Golsa Tahmasebzadeh +4
In this paper, we introduce the MLM (Multiple Languages and Modalities) dataset - a new resource to train and evaluate multitask systems on samples in multiple modalities and three…
Training Multimodal Systems for Classification with Multiple Objectives
Jason Armitage, Shramana Thakur, Rishi Tripathi +2
We learn about the world from a diverse range of sensory information. Automated systems lack this ability as investigation has centred on processing information presented in a sing…