4 citations · 10 across the 8 of their papers we have counts for
10 papers
DCTM: Dilated Convolutional Transformer Model for Multimodal Engagement Estimation in Conversation
Vu Ngoc Tu, Van Thong Huynh, Hyung-Jeong Yang +4
Conversational engagement estimation is posed as a regression problem, entailing the identification of the favorable attention and involvement of the participants in the conversati…
Speaker Recognition in Realistic Scenario Using Multimodal Data
Saqlain Hussain Shah, Muhammad Saad Saeed, Shah Nawaz +1
In recent years, an association is established between faces and voices of celebrities leveraging large scale audio-visual information from YouTube. The availability of large scale…
Learning Branched Fusion and Orthogonal Projection for Face-Voice Association
Muhammad Saad Saeed, Shah Nawaz, Muhammad Haris Khan +3
Recent years have seen an increased interest in establishing association between faces and voices of celebrities leveraging audio-visual information from YouTube. Prior works adopt…
Guiding Attention using Partial-Order Relationships for Image Captioning
Murad Popattia, Muhammad Rafi, Rizwan Qureshi +1
The use of attention models for automated image captioning has enabled many systems to produce accurate and meaningful descriptions for images. Over the years, many novel approache…
Semantically Grounded Visual Embeddings for Zero-Shot Learning
Shah Nawaz, Jacopo Cavazza, Alessio Del Bue
Zero-shot learning methods rely on fixed visual and semantic embeddings, extracted from independent vision and language models, both pre-trained for other large-scale tasks. This i…
Picture What you Read
Ignazio Gallo, Shah Nawaz, Alessandro Calefati +2
Visualization refers to our ability to create an image in our head based on the text we read or the words we hear. It is one of the many skills that makes reading comprehension pos…
Do Cross Modal Systems Leverage Semantic Relationships?
Shah Nawaz, Muhammad Kamran Janjua, Ignazio Gallo +3
Current cross-modal retrieval systems are evaluated using R@K measure which does not leverage semantic relationships rather strictly follows the manually marked image text query pa…
Learning Inward Scaled Hypersphere Embedding: Exploring Projections in Higher Dimensions
Muhammad Kamran Janjua, Shah Nawaz, Alessandro Calefati +1
Majority of the current dimensionality reduction or retrieval techniques rely on embedding the learned feature representations onto a computable metric space. Once the learned feat…
Seeing Colors: Learning Semantic Text Encoding for Classification
Shah Nawaz, Alessandro Calefati, Muhammad Kamran Janjua +1
The question we answer with this work is: can we convert a text document into an image to exploit best image classification models to classify documents? To answer this question we…
Revisiting Cross Modal Retrieval
Shah Nawaz, Muhammad Kamran Janjua, Alessandro Calefati +1
This paper proposes a cross-modal retrieval system that leverages on image and text encoding. Most multimodal architectures employ separate networks for each modality to capture th…