8 citations · 16 across the 15 of their papers we have counts for
9 papers · 1 filter
GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editing
Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood +2
Data augmentation is widely used to enhance generalization in visual classification tasks. However, traditional methods struggle when source and target domains differ, as in domain…
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…
A Survey of the Self Supervised Learning Mechanisms for Vision Transformers
Asifullah Khan, Anabia Sohail, Mustansar Fiaz +11
Advances in deep learning are re-defining how visual data is processed and understand by the machines. Vision Transformers (ViTs) have recently demonstrated prominent performance i…
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…
Exploiting Autoencoder's Weakness to Generate Pseudo Anomalies
Marcella Astrid, Muhammad Zaigham Zaheer, Djamila Aouada +1
Due to the rare occurrence of anomalous events, a typical approach to anomaly detection is to train an autoencoder (AE) with normal data only so that it learns the patterns or repr…
DiffuseMix: Label-Preserving Data Augmentation with Diffusion Models
Khawar Islam, Muhammad Zaigham Zaheer, Arif Mahmood +1
Recently, a number of image-mixing-based augmentation techniques have been introduced to improve the generalization of deep neural networks. In these techniques, two or more random…
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…
Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline
Anas Al-lahham, Muhammad Zaigham Zaheer, Nurbek Tastan +1
Unsupervised (US) video anomaly detection (VAD) in surveillance applications is gaining more popularity recently due to its practical real-world applications. As surveillance video…
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data
Marcella Astrid, Muhammad Zaigham Zaheer, Seung-Ik Lee
In order to devise an anomaly detection model using only normal training data, an autoencoder (AE) is typically trained to reconstruct the data. As a result, the AE can extract nor…