36 citations · 74 across the 12 of their papers we have counts for
19 papers
Flow-of-Thought: A Framework for Visual Reasoning
Mariia Baidachna, Nicolas Pugeault
Mental imagery, ``seeing with the mind's eye'' is an essential aspect of human cognition. Despite rapid progress Large Language Models (LLMs) and Vision Transformers (ViTs) still u…
Promptable Animal Pose Tracking Across Species
Le Li, Daniela Ivanova, Nicolas Pugeault
Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated approaches are imperative.…
Modeling 3D Pedestrian-Vehicle Interactions for Vehicle-Conditioned Pose Forecasting
Guangxun Zhu, Xuan Liu, Nicolas Pugeault +2
Accurately predicting pedestrian motion is crucial for safe and reliable autonomous driving in complex urban environments. In this work, we present a 3D vehicle-conditioned pedestr…
The role of noise in denoising models for anomaly detection in medical images
Antanas Kascenas, Pedro Sanchez, Patrick Schrempf +9
Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are dif…
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data
Charlie Kirkwood, Theo Economou, Henry Odbert +1
As the costs of sensors and associated IT infrastructure decreases - as exemplified by the Internet of Things - increasing volumes of observational data are becoming available for…
Transformer-Encoder Detector Module: Using Context to Improve Robustness to Adversarial Attacks on Object Detection
Faisal Alamri, Sinan Kalkan, Nicolas Pugeault
Deep neural network approaches have demonstrated high performance in object recognition (CNN) and detection (Faster-RCNN) tasks, but experiments have shown that such architectures…
Bayesian deep learning for mapping via auxiliary information: a new era for geostatistics?
Charlie Kirkwood, Theo Economou, Nicolas Pugeault
For geospatial modelling and mapping tasks, variants of kriging - the spatial interpolation technique developed by South African mining engineer Danie Krige - have long been regard…
A framework for probabilistic weather forecast post-processing across models and lead times using machine learning
Charlie Kirkwood, Theo Economou, Henry Odbert +1
Forecasting the weather is an increasingly data intensive exercise. Numerical Weather Prediction (NWP) models are becoming more complex, with higher resolutions, and there are incr…
Real-time Facial Expression Recognition "In The Wild'' by Disentangling 3D Expression from Identity
Mohammad Rami Koujan, Luma Alharbawee, Giorgos Giannakakis +2
Human emotions analysis has been the focus of many studies, especially in the field of Affective Computing, and is important for many applications, e.g. human-computer intelligent…
Image Captioning through Image Transformer
Sen He, Wentong Liao, Hamed R. Tavakoli +3
Automatic captioning of images is a task that combines the challenges of image analysis and text generation. One important aspect in captioning is the notion of attention: How to d…
Contextual Relabelling of Detected Objects
Faisal Alamri, Nicolas Pugeault
Contextual information, such as the co-occurrence of objects and the spatial and relative size among objects provides deep and complex information about scenes. It also can play an…
Understanding and Visualizing Deep Visual Saliency Models
Sen He, Hamed R. Tavakoli, Ali Borji +2
Recently, data-driven deep saliency models have achieved high performance and have outperformed classical saliency models, as demonstrated by results on datasets such as the MIT300…
Human Attention in Image Captioning: Dataset and Analysis
Sen He, Hamed R. Tavakoli, Ali Borji +1
In this work, we present a novel dataset consisting of eye movements and verbal descriptions recorded synchronously over images. Using this data, we study the differences in human…
On-Policy Trust Region Policy Optimisation with Replay Buffers
Dmitry Kangin, Nicolas Pugeault
Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from sev…
What Catches the Eye? Visualizing and Understanding Deep Saliency Models
Sen He, Ali Borji, Yang Mi +1
Deep convolutional neural networks have demonstrated high performances for fixation prediction in recent years. How they achieve this, however, is less explored and they remain to…
Aggregated Sparse Attention for Steering Angle Prediction
Sen He, Dmitry Kangin, Yang Mi +1
In this paper, we apply the attention mechanism to autonomous driving for steering angle prediction. We propose the first model, applying the recently introduced sparse attention m…
Salient Region Segmentation
Sen He, Nicolas Pugeault
Saliency prediction is a well studied problem in computer vision. Early saliency models were based on low-level hand-crafted feature derived from insights gained in neuroscience an…
Deep saliency: What is learnt by a deep network about saliency?
Sen He, Nicolas Pugeault
Deep convolutional neural networks have achieved impressive performance on a broad range of problems, beating prior art on established benchmarks, but it often remains unclear what…
SeDAR - Semantic Detection and Ranging: Humans can localise without LiDAR, can robots?
Oscar Mendez, Simon Hadfield, Nicolas Pugeault +1
How does a person work out their location using a floorplan? It is probably safe to say that we do not explicitly measure depths to every visible surface and try to match them agai…