10 citations · 15 across the 26 of their papers we have counts for
21 papers · 1 filter
Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge Evaluation Plan
Marta Moscati, Swapnil Khandoker, Muhammad Saad Saeed +8
Face--voice association models may rely on language or gender cues in the voice rather than on speaker-specific voice characteristics, which can lead to a performance deterioration…
Learning Speaker Identity Beyond Language and Modality Constraints: Insights from the POLY-SIM 2026 Challenge
Marta Moscati, Muhammad Saad Saeed, Marina Zanoni +9
Multimodal speaker identification systems typically assume the availability of complete and homogeneous audio-visual modalities during both training and testing, and assume each sp…
SB-BEVFusion: Enhancing the Robustness against Sensor Malfunction and Corruptions
Markus Essl, Marta Moscati, Mubashir Noman +4
Multimodal sensor fusion has demonstrated remarkable performance improvements over unimodal approaches in 3D object detection for autonomous vehicles. Typically, existing methods t…
POLY-SIM: Polyglot Speaker Identification with Missing Modality Grand Challenge 2026 Evaluation Plan
Marta Moscati, Muhammad Saad Saeed, Marina Zanoni +8
Multimodal speaker identification systems typically assume the availability of complete and homogeneous audio-visual modalities during both training and testing. However, in real-w…
EoCD: Encoder only Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hiyam Debary +4
Being a cornerstone of temporal analysis, change detection has been playing a pivotal role in modern earth observation. Existing change detection methods rely on the Siamese encode…
Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learning
Felix Breiteneder, Mohammad Belal, Muhammad Saad Saeed +5
Internet memes are powerful tools for communication, capable of spreading political, psychological, and sociocultural ideas. However, they can be harmful and can be used to dissemi…
Face-Voice Association with Inductive Bias for Maximum Class Separation
Marta Moscati, Oleksandr Kats, Mubashir Noman +4
Face-voice association is widely studied in multimodal learning and is approached representing faces and voices with embeddings that are close for a same person and well separated…
Linking Faces and Voices Across Languages: Insights from the FAME 2026 Challenge
Marta Moscati, Ahmed Abdullah, Muhammad Saad Saeed +7
Over half of the world's population is bilingual and people often communicate under multilingual scenarios. The Face-Voice Association in Multilingual Environments (FAME) 2026 Chal…
Face-voice Association in Multilingual Environments (FAME) 2026 Challenge Evaluation Plan
Marta Moscati, Ahmed Abdullah, Muhammad Saad Saeed +7
The advancements of technology have led to the use of multimodal systems in various real-world applications. Among them, audio-visual systems are among the most widely used multimo…
PAEFF: Precise Alignment and Enhanced Gated Feature Fusion for Face-Voice Association
Abdul Hannan, Muhammad Arslan Manzoor, Shah Nawaz +3
We study the task of learning association between faces and voices, which is gaining interest in the multimodal community lately. These methods suffer from the deliberate crafting…
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models
Abdul Hannan, Alessio Brutti, Shah Nawaz +1
Recent advancement in deep learning encouraged developing large automatic speech recognition (ASR) models that achieve promising results while ignoring computational and memory con…
Modality Invariant Multimodal Learning to Handle Missing Modalities: A Single-Branch Approach
Muhammad Saad Saeed, Shah Nawaz, Muhammad Zaigham Zaheer +6
Multimodal networks have demonstrated remarkable performance improvements over their unimodal counterparts. Existing multimodal networks are designed in a multi-branch fashion that…
Chameleon: Images Are What You Need For Multimodal Learning Robust To Missing Modalities
Muhammad Irzam Liaqat, Shah Nawaz, Muhammad Zaigham Zaheer +5
Multimodal learning has demonstrated remarkable performance improvements over unimodal architectures. However, multimodal learning methods often exhibit deteriorated performances i…
Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan
Muhammad Saad Saeed, Shah Nawaz, Muhammad Salman Tahir +7
The advancements of technology have led to the use of multimodal systems in various real-world applications. Among them, the audio-visual systems are one of the widely used multimo…
Single-branch Network for Multimodal Training
Muhammad Saad Saeed, Shah Nawaz, Muhammad Haris Khan +4
With the rapid growth of social media platforms, users are sharing billions of multimedia posts containing audio, images, and text. Researchers have focused on building autonomous…
Fusion and Orthogonal Projection for Improved Face-Voice Association
Muhammad Saad Saeed, Muhammad Haris Khan, Shah Nawaz +2
We study the problem of learning association between face and voice, which is gaining interest in the computer vision community lately. Prior works adopt pairwise or triplet loss f…
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…
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…
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…
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…
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…