342 citations · 787 across the 44 of their papers we have counts for
51 papers
R-CNN-Based Chess Position Recognition
Paras Govind, Ognjen Arandjelović
Performing chess game position recognition solely from a single image of a three-dimensional board requires predicting the position and orientation of the board relative to the cam…
Multimodal Latent Emotion Recognition from Micro-expression and Physiological Signals
Liangfei Zhang, Yifei Qian, Ognjen Arandjelovic +1
This paper discusses the benefits of incorporating multimodal data for improving latent emotion recognition accuracy, focusing on micro-expression (ME) and physiological signals (P…
A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification Models
Zhongliang Guo, Weiye Li, Yifei Qian +2
In this paper, we tackle the challenge of white-box false positive adversarial attacks on contrastive loss based offline handwritten signature verification models. We propose a nov…
Deep Multiple Instance Learning with Distance-Aware Self-Attention
Georg Wölflein, Lucie Charlotte Magister, Pietro Liò +2
Traditional supervised learning tasks require a label for every instance in the training set, but in many real-world applications, labels are only available for collections (bags)…
HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks
Georg Wölflein, In Hwa Um, David J Harrison +1
The presence and density of specific types of immune cells are important to understand a patient's immune response to cancer. However, immunofluorescence staining required to ident…
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss
Haseeb Nazki, Ognjen Arandjelović, InHwa Um +1
Histopathology relies on the analysis of microscopic tissue images to diagnose disease. A crucial part of tissue preparation is staining whereby a dye is used to make the salient t…
COVID-19 and Science Communication: The Recording and Reporting of Disease Mortality
Ognjen Arandjelovic
The ongoing COVID-19 pandemic has brought science to the fore of the public discourse and considering the complexity of the issues involved, with it also the challenge of effective…
Magnifying Networks for Images with Billions of Pixels
Neofytos Dimitriou, Ognjen Arandjelovic
The shift towards end-to-end deep learning has brought unprecedented advances in many areas of computer vision. However, deep neural networks are trained on images with resolutions…
Short and Long Range Relation Based Spatio-Temporal Transformer for Micro-Expression Recognition
Liangfei Zhang, Xiaopeng Hong, Ognjen Arandjelovic +1
Being spontaneous, micro-expressions are useful in the inference of a person's true emotions even if an attempt is made to conceal them. Due to their short duration and low intensi…
Hoechst Is All You Need: Lymphocyte Classification with Deep Learning
Jessica Cooper, In Hwa Um, Ognjen Arandjelović +1
Multiplex immunofluorescence and immunohistochemistry benefit patients by allowing cancer pathologists to identify several proteins expressed on the surface of cells, enabling cell…
Determining Chess Game State From an Image
Georg Wölflein, Ognjen Arandjelović
Identifying the configuration of chess pieces from an image of a chessboard is a problem in computer vision that has not yet been solved accurately. However, it is important for he…
Believe The HiPe: Hierarchical Perturbation for Fast, Robust, and Model-Agnostic Saliency Mapping
Jessica Cooper, Ognjen Arandjelović, David J Harrison
Understanding the predictions made by Artificial Intelligence (AI) systems is becoming more and more important as deep learning models are used for increasingly complex and high-st…
A New Look at Ghost Normalization
Neofytos Dimitriou, Ognjen Arandjelovic
Batch normalization (BatchNorm) is an effective yet poorly understood technique for neural network optimization. It is often assumed that the degradation in BatchNorm performance t…
Deep Learning for Whole Slide Image Analysis: An Overview
Neofytos Dimitriou, Ognjen Arandjelović, Peter D Caie
The widespread adoption of whole slide imaging has increased the demand for effective and efficient gigapixel image analysis. Deep learning is at the forefront of computer vision,…
Understanding Ancient Coin Images
Jessica Cooper, Ognjen Arandjelovic
In recent years, a range of problems within the broad umbrella of automatic, computer vision based analysis of ancient coins has been attracting an increasing amount of attention.…
Colorectal Cancer Outcome Prediction from H&E Whole Slide Images using Machine Learning and Automatically Inferred Phenotype Profiles
Xingzhi Yue, Neofytos Dimitriou, Ognjen Arandjelovic
Digital pathology (DP) is a new research area which falls under the broad umbrella of health informatics. Owing to its potential for major public health impact, in recent years DP…
Synthesising Wider Field Images from Narrow-Field Retinal Video Acquired Using a Low-Cost Direct Ophthalmoscope (Arclight) Attached to a Smartphone
Keylor Daniel Chaves Viquez, Ognjen Arandjelovic, Andrew Blaikie +1
Access to low cost retinal imaging devices in low and middle income countries is limited, compromising progress in preventing needless blindness. The Arclight is a recently develop…
Prediction of future hospital admissions - what is the tradeoff between specificity and accuracy?
Ieva Vasiljeva, Ognjen Arandjelovic
Large amounts of electronic medical records collected by hospitals across the developed world offer unprecedented possibilities for knowledge discovery using computer based data mi…
Identification of promising research directions using machine learning aided medical literature analysis
Victor Andrei, Ognjen Arandjelovic
The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected da…
Achieving stable subspace clustering by post-processing generic clustering results
Duc-Son Pham, Ognjen Arandjelovic, Svetha Venkatesh
We propose an effective subspace selection scheme as a post-processing step to improve results obtained by sparse subspace clustering (SSC). Our method starts by the computation of…
Learnt quasi-transitive similarity for retrieval from large collections of faces
Ognjen Arandjelovic
We are interested in identity-based retrieval of face sets from large unlabelled collections acquired in uncontrolled environments. Given a baseline algorithm for measuring the sim…
Highly accurate gaze estimation using a consumer RGB-depth sensor
Reza Shoja Ghiass, Ognjen Arandjelovic
Determining the direction in which a person is looking is an important problem in a wide range of HCI applications. In this paper we describe a highly accurate algorithm that perfo…
Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device
Warren Rieutort-Louis, Ognjen Arandjelovic
Visual recognition and vision based retrieval of objects from large databases are tasks with a wide spectrum of potential applications. In this paper we propose a novel recognition…
Discovering topic structures of a temporally evolving document corpus
Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Phung +1
In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimens…