9 citations · 9 across the 4 of their papers we have counts for
6 papers
SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition
Ning Wang, Tieyue Wu, Naeha Sharif +5
Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typ…
Fact or Fake? Assessing the Role of Deepfake Detectors in Multimodal Misinformation Detection
A S M Sharifuzzaman Sagar, Mohammed Bennamoun, Farid Boussaid +4
In multimodal misinformation, deception usually arises not just from pixel-level manipulations in an image, but from the semantic and contextual claim jointly expressed by the imag…
Multimodal Neuroimaging Attention-Based architecture for Cognitive Decline Prediction
Jamie Vo, Naeha Sharif, Ghulam Mubashar Hassan
The early detection of Alzheimer's Disease is imperative to ensure early treatment and improve patient outcomes. There has consequently been extenstive research into detecting AD a…
WEmbSim: A Simple yet Effective Metric for Image Captioning
Naeha Sharif, Lyndon White, Mohammed Bennamoun +2
The area of automatic image caption evaluation is still undergoing intensive research to address the needs of generating captions which can meet adequacy and fluency requirements.…
LCEval: Learned Composite Metric for Caption Evaluation
Naeha Sharif, Lyndon White, Mohammed Bennamoun +2
Automatic evaluation metrics hold a fundamental importance in the development and fine-grained analysis of captioning systems. While current evaluation metrics tend to achieve an a…
SubICap: Towards Subword-informed Image Captioning
Naeha Sharif, Mohammed Bennamoun, Wei Liu +1
Existing Image Captioning (IC) systems model words as atomic units in captions and are unable to exploit the structural information in the words. This makes representation of rare…