446 citations · 763 across the 21 of their papers we have counts for
22 papers
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition
Cong Wu, Xiao-Jun Wu, Josef Kittler +4
Contrastive learning has achieved great success in skeleton-based action recognition. However, most existing approaches encode the skeleton sequences as entangled spatiotemporal re…
Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding
Jiantao Wu, Shentong Mo, Muhammad Awais +3
Self-supervised pretraining (SSP) has emerged as a popular technique in machine learning, enabling the extraction of meaningful feature representations without labelled data. In th…
FROD: Robust Object Detection for Free
Muhammad, Awais, Weiming +5
Object detection is a vital task in computer vision and has become an integral component of numerous critical systems. However, state-of-the-art object detectors, similar to their…
Foundational Models Defining a New Era in Vision: A Survey and Outlook
Muhammad Awais, Muzammal Naseer, Salman Khan +5
Vision systems to see and reason about the compositional nature of visual scenes are fundamental to understanding our world. The complex relations between objects and their locatio…
ASiT: Local-Global Audio Spectrogram vIsion Transformer for Event Classification
Sara Atito, Muhammad Awais, Wenwu Wang +2
Transformers, which were originally developed for natural language processing, have recently generated significant interest in the computer vision and audio communities due to thei…
GMML is All you Need
Sara Atito, Muhammad Awais, Josef Kittler
Vision transformers have generated significant interest in the computer vision community because of their flexibility in exploiting contextual information, whether it is sharply co…
MC-SSL0.0: Towards Multi-Concept Self-Supervised Learning
Sara Atito, Muhammad Awais, Ammarah Farooq +2
Self-supervised pretraining is the method of choice for natural language processing models and is rapidly gaining popularity in many vision tasks. Recently, self-supervised pretrai…
Global Interaction Modelling in Vision Transformer via Super Tokens
Ammarah Farooq, Muhammad Awais, Sara Ahmed +1
With the popularity of Transformer architectures in computer vision, the research focus has shifted towards developing computationally efficient designs. Window-based local attenti…
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Muhammad Awais, Fengwei Zhou, Chuanlong Xie +3
Deep neural networks are susceptible to adversarially crafted, small and imperceptible changes in the natural inputs. The most effective defense mechanism against these examples is…
Adversarial Robustness for Unsupervised Domain Adaptation
Muhammad Awais, Fengwei Zhou, Hang Xu +4
Extensive Unsupervised Domain Adaptation (UDA) studies have shown great success in practice by learning transferable representations across a labeled source domain and an unlabeled…
SiT: Self-supervised vIsion Transformer
Sara Atito, Muhammad Awais, Josef Kittler
Self-supervised learning methods are gaining increasing traction in computer vision due to their recent success in reducing the gap with supervised learning. In natural language pr…
NPT-Loss: A Metric Loss with Implicit Mining for Face Recognition
Syed Safwan Khalid, Muhammad Awais, Chi-Ho Chan +4
Face recognition (FR) using deep convolutional neural networks (DCNNs) has seen remarkable success in recent years. One key ingredient of DCNN-based FR is the appropriate design of…
AXM-Net: Implicit Cross-Modal Feature Alignment for Person Re-identification
Ammarah Farooq, Muhammad Awais, Josef Kittler +1
Cross-modal person re-identification (Re-ID) is critical for modern video surveillance systems. The key challenge is to align cross-modality representations induced by the semantic…
A Flatter Loss for Bias Mitigation in Cross-dataset Facial Age Estimation
Ali Akbari, Muhammad Awais, Zhen-Hua Feng +2
The most existing studies in the facial age estimation assume training and test images are captured under similar shooting conditions. However, this is rarely valid in real-world a…
Deep Convolutional Neural Network Ensembles using ECOC
Sara Atito Ali Ahmed, Cemre Zor, Berrin Yanikoglu +2
Deep neural networks have enhanced the performance of decision making systems in many applications including image understanding, and further gains can be achieved by constructing…
Towards an Adversarially Robust Normalization Approach
Muhammad Awais, Fahad Shamshad, Sung-Ho Bae
Batch Normalization (BatchNorm) is effective for improving the performance and accelerating the training of deep neural networks. However, it has also shown to be a cause of advers…
A Convolutional Baseline for Person Re-Identification Using Vision and Language Descriptions
Ammarah Farooq, Muhammad Awais, Fei Yan +3
Classical person re-identification approaches assume that a person of interest has appeared across different cameras and can be queried by one of the existing images. However, in r…
Leveraging Deep Stein's Unbiased Risk Estimator for Unsupervised X-ray Denoising
Fahad Shamshad, Muhammad Awais, Muhammad Asim +3
Among the plethora of techniques devised to curb the prevalence of noise in medical images, deep learning based approaches have shown the most promise. However, one critical limita…
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
Zhen-Hua Feng, Josef Kittler, Muhammad Awais +2
We present a new loss function, namely Wing loss, for robust facial landmark localisation with Convolutional Neural Networks (CNNs). We first compare and analyse different loss fun…
3D Morphable Models as Spatial Transformer Networks
Anil Bas, Patrik Huber, William A. P. Smith +2
In this paper, we show how a 3D Morphable Model (i.e. a statistical model of the 3D shape of a class of objects such as faces) can be used to spatially transform input data as a mo…
Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild
Zhen-Hua Feng, Josef Kittler, Muhammad Awais +2
We present a framework for robust face detection and landmark localisation of faces in the wild, which has been evaluated as part of `the 2nd Facial Landmark Localisation Competiti…
Medical Image Retrieval using Deep Convolutional Neural Network
Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais +1
With a widespread use of digital imaging data in hospitals, the size of medical image repositories is increasing rapidly. This causes difficulty in managing and querying these larg…