activity
20182024
most citedA Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios

2 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.IR20242 cited

A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios

Christian Ganhör, Marta Moscati, Anna Hausberger +2

Most recommender systems adopt collaborative filtering (CF) and provide recommendations based on past collective interactions. Therefore, the performance of CF algorithms degrades…

cs.CV2020

Cross-modal Speaker Verification and Recognition: A Multilingual Perspective

Muhammad Saad Saeed, Shah Nawaz, Pietro Morerio +4

Recent years have seen a surge in finding association between faces and voices within a cross-modal biometric application along with speaker recognition. Inspired from this, we int…

cs.CV2019

Deep Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals

Shah Nawaz, Muhammad Kamran Janjua, Ignazio Gallo +2

We propose a novel deep training algorithm for joint representation of audio and visual information which consists of a single stream network (SSNet) coupled with a novel loss func…

cs.CV2019

Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition

Omer Arshad, Ignazio Gallo, Shah Nawaz +1

With massive explosion of social media such as Twitter and Instagram, people daily share billions of multimedia posts, containing images and text. Typically, text in these posts is…

cs.CV2018

Image and Encoded Text Fusion for Multi-Modal Classification

Ignazio Gallo, Alessandro Calefati, Shah Nawaz +1

Multi-modal approaches employ data from multiple input streams such as textual and visual domains. Deep neural networks have been successfully employed for these approaches. In thi…

cs.CV2018

Git Loss for Deep Face Recognition

Alessandro Calefati, Muhammad Kamran Janjua, Shah Nawaz +1

Convolutional Neural Networks (CNNs) have been widely used in computer vision tasks, such as face recognition and verification, and have achieved state-of-the-art results due to th…