1.1k citations · 4k across the 76 of their papers we have counts for
80 papers
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…
FusionBooster: A Unified Image Fusion Boosting Paradigm
Chunyang Cheng, Tianyang Xu, Xiao-Jun Wu +3
In recent years, numerous ideas have emerged for designing a mutually reinforcing mechanism or extra stages for the image fusion task, ignoring the inevitable gaps between differen…
LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images
Hui Li, Tianyang Xu, Xiao-Jun Wu +2
Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role…
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…
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object Tracking
Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang +5
RGB-D object tracking has attracted considerable attention recently, achieving promising performance thanks to the symbiosis between visual and depth channels. However, given a lim…
DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification
Rui Wang, Xiao-Jun Wu, Ziheng Chen +2
Image set-based visual classification methods have achieved remarkable performance, via characterising the image set in terms of a non-singular covariance matrix on a symmetric pos…
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…
Importance Weighted Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
Scene graph generation is a structured prediction task aiming to explicitly model objects and their relationships via constructing a visually-grounded scene graph for an input imag…
Constrained Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
As a structured prediction task, scene graph generation aims to build a visually-grounded scene graph to explicitly model objects and their relationships in an input image. Current…
Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
Zhangyong Tang, Tianyang Xu, Hui Li +3
We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrare…
Riemannian Local Mechanism for SPD Neural Networks
Ziheng Chen, Tianyang Xu, Xiao-Jun Wu +3
The Symmetric Positive Definite (SPD) matrices have received wide attention for data representation in many scientific areas. Although there are many different attempts to develop…
Neural Belief Propagation for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
Scene graph generation aims to interpret an input image by explicitly modelling the potential objects and their relationships, which is predominantly solved by the message passing…
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…
Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms
Norman Poh, Thirimachos Bourlai, Josef Kittler +13
Automatically verifying the identity of a person by means of biometrics is an important application in day-to-day activities such as accessing banking services and security control…
Video Is Graph: Structured Graph Module for Video Action Recognition
Rongchang Li, Xiao-Jun Wu, Tianyang Xu
In the field of action recognition, video clips are always treated as ordered frames for subsequent processing. To achieve spatio-temporal perception, existing approaches propose t…
Learning PAC-Bayes Priors for Probabilistic Neural Networks
Maria Perez-Ortiz, Omar Rivasplata, Benjamin Guedj +5
Recent works have investigated deep learning models trained by optimising PAC-Bayes bounds, with priors that are learnt on subsets of the data. This combination has been shown to l…
MOON: Multi-Hash Codes Joint Learning for Cross-Media Retrieval
Donglin Zhang, Xiao-Jun Wu, He-Feng Yin +1
In recent years, cross-media hashing technique has attracted increasing attention for its high computation efficiency and low storage cost. However, the existing approaches still h…
UMFA: A photorealistic style transfer method based on U-Net and multi-layer feature aggregation
D. Y. Rao, X. J. Wu, H. Li +2
In this paper, we propose a photorealistic style transfer network to emphasize the natural effect of photorealistic image stylization. In general, distortion of the image content a…
PPT Fusion: Pyramid Patch Transformerfor a Case Study in Image Fusion
Yu Fu, TianYang Xu, XiaoJun Wu +1
The Transformer architecture has witnessed a rapid development in recent years, outperforming the CNN architectures in many computer vision tasks, as exemplified by the Vision Tran…
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…
RFN-Nest: An end-to-end residual fusion network for infrared and visible images
Hui Li, Xiao-Jun Wu, Josef Kittler
In the image fusion field, the design of deep learning-based fusion methods is far from routine. It is invariably fusion-task specific and requires a careful consideration. The mos…
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…
Differentiable Neural Architecture Learning for Efficient Neural Network Design
Qingbei Guo, Xiao-Jun Wu, Josef Kittler +1
Automated neural network design has received ever-increasing attention with the evolution of deep convolutional neural networks (CNNs), especially involving their deployment on emb…