10 citations · 14 across the 17 of their papers we have counts for
20 papers
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…
Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background
Mamoona Javaid, Mubashir Noman, Abdul Hannan +3
Rapid expansion of urban areas and population growth is causing an immense increase in waste production, which demands the need for efficient and automated waste management. In thi…
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…
Distillation-based Layer Dropping (DLD): Effective End-to-end Framework for Dynamic Speech Networks
Abdul Hannan, Daniele Falavigna, Shah Nawaz +3
Edge devices operate in constrained and varying resource settings, requiring dynamic architectures that can adapt to limitations of the available resources. To meet such demands, l…
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…
RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association
Abdul Hannan, Furqan Malik, Hina Jabbar +2
Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-Ger…
HyRet-Change: A hybrid retentive network for remote sensing change detection
Mustansar Fiaz, Mubashir Noman, Hiyam Debary +2
Recently convolution and transformer-based change detection (CD) methods provide promising performance. However, it remains unclear how the local and global dependencies interact t…
InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation
Daniya Najiha Abdul Kareem, Abdul Hannan, Mubashir Noman +3
Accurate microscopic medical image segmentation plays a crucial role in diagnosing various cancerous cells and identifying tumors. Driven by advancements in deep learning, convolut…
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…
COSNet: A Novel Semantic Segmentation Network using Enhanced Boundaries in Cluttered Scenes
Muhammad Ali, Mamoona Javaid, Mubashir Noman +2
Automated waste recycling aims to efficiently separate the recyclable objects from the waste by employing vision-based systems. However, the presence of varying shaped objects havi…
CDChat: A Large Multimodal Model for Remote Sensing Change Description
Mubashir Noman, Noor Ahsan, Muzammal Naseer +4
Large multimodal models (LMMs) have shown encouraging performance in the natural image domain using visual instruction tuning. However, these LMMs struggle to describe the content…
FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Background
Muhammad Ali, Mamoona Javaid, Mubashir Noman +2
Existing deep learning approaches leave out the semantic cues that are crucial in semantic segmentation present in complex scenarios including cluttered backgrounds and translucent…
ELGC-Net: Efficient Local-Global Context Aggregation for Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +2
Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired…
Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery
Mubashir Noman, Muzammal Naseer, Hisham Cholakkal +3
Recent advances in unsupervised learning have demonstrated the ability of large vision models to achieve promising results on downstream tasks by pre-training on large amount of un…
Remote Sensing Change Detection With Transformers Trained from Scratch
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +4
Current transformer-based change detection (CD) approaches either employ a pre-trained model trained on large-scale image classification ImageNet dataset or rely on first pre-train…
AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility
Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha +7
One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing b…