Skip to main content

Research Repository

Advanced Search

All Outputs (87)

An Almost Singularly Optimal Asynchronous Distributed MST Algorithm (2022)
Presentation / Conference Contribution
Dufoulon, F., Kutten, S., Moses Jr., W. K., Pandurangan, G., & Peleg, D. (2022, December). An Almost Singularly Optimal Asynchronous Distributed MST Algorithm. Presented at 36th International Symposium on Distributed Computing (DISC 2022)

Package Delivery Using Drones with Restricted Movement Areas (2022)
Presentation / Conference Contribution
Erlebach, T., Luo, K., & Spieksma, F. C. (2022, December). Package Delivery Using Drones with Restricted Movement Areas. Presented at 33rd International Symposium on Algorithms and Computation (ISAAC 2022), Seoul, Korea

Denoising Diffusion Probabilistic Models for Styled Walking Synthesis (2022)
Presentation / Conference Contribution
Findlay, E., Zhang, H., Chang, Z., & Shum, H. P. (2022, November). Denoising Diffusion Probabilistic Models for Styled Walking Synthesis. Presented at MIG 2022: The 15th Annual ACM SIGGRAPH Conference on Motion, Interaction and Games, Guanajuato, Mexico

Generating realistic motions for digital humans is time-consuming for many graphics applications. Data-driven motion synthesis approaches have seen solid progress in recent years through deep generative models. These results offer high-quality motion... Read More about Denoising Diffusion Probabilistic Models for Styled Walking Synthesis.

Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment (2022)
Presentation / Conference Contribution
Leach, A., Schmon, S. M., Degiacomi, M. T., & Willcocks, C. G. (2022, April). Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment. Presented at ICLR 2022 Workshop on Geometrical and Topological Representation Learning

Probabilistic diffusion models are capable of modeling complex data distributions on high-dimensional Euclidean spaces for a range applications. However, many real world tasks involve more complex structures such as data distributions defined on mani... Read More about Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment.

Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention (2022)
Presentation / Conference Contribution
Sun, Z., Harit, A., Cristea, A. I., Yu, J., Al Moubayed, N., & Shi, L. (2022, December). Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention. Presented at IEEE Big Data, Osaka, Japan

Medical visual question answering (Med-VQA) is to answer medical questions based on clinical images provided. This field is still in its infancy due to the complexity of the trio formed of questions, multimodal features and expert knowledge. In this... Read More about Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention.

Aesthetic Enhancement via Color Area and Location Awareness (2022)
Presentation / Conference Contribution
Yang, B., Wang, Q., Li, F. W., Liang, X., Wei, T., & Zhu, C. (2022, October). Aesthetic Enhancement via Color Area and Location Awareness. Presented at The 30th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2022, Kyoto, Japan

Choosing a suitable color palette can typically improve image aesthetic, where a naive way is choosing harmonious colors from some pre-defined color combinations in color wheels. However, color palettes only consider the usage of color types without... Read More about Aesthetic Enhancement via Color Area and Location Awareness.

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty (2022)
Presentation / Conference Contribution
Erlebach, T., de Lima, M. S., Megow, N., & Schlöter, J. (2022, September). Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty. Presented at 30th Annual European Symposium on Algorithms (ESA 2022), Potsdam, Germany

We study how to utilize (possibly erroneous) predictions in a model for computing under uncertainty in which an algorithm can query unknown data. Our aim is to minimize the number of queries needed to solve the minimum spanning tree problem, a fundam... Read More about Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty.

Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery (2022)
Presentation / Conference Contribution
Bhowmik, N., & Breckon, T. (2022, December). Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery. Presented at International Conference on Machine Learning Applications, Bahamas

X-ray baggage security screening is in widespread use and crucial to maintaining transport security for threat/anomaly detection tasks. The automatic detection of anomaly, which is concealed within cluttered and complex electronics/electrical items,... Read More about Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery.

UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery (2022)
Presentation / Conference Contribution
Organisciak, D., Poyser, M., Alsehaim, A., Hu, S., Isaac-Medina, B. K., Breckon, T. P., & Shum, H. P. UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery. Presented at 2022 17th International Conference on Computer Vision Theory and Applications

As unmanned aerial vehicles (UAV) become more accessible with a growing range of applications, the risk of UAV disruption increases. Recent development in deep learning allows vision-based counter-UAV systems to detect and track UAVs with a single ca... Read More about UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery.

Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry (2022)
Presentation / Conference Contribution
Hodgson, R., Wang, J., Cristea, A. I., & Graham, J. (2022, December). Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry. Presented at 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Phuket, Thailand

Barriers to the delivery of journalistic content to suitable media outlets present difficulties to both journalists and publishing houses. These may take the form of barriers to the identification of key individuals to whom the content is relevant, a... Read More about Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry.

Gamifying Experiential Learning Theory (2022)
Presentation / Conference Contribution
Alsaqqaf, A., & Li, F. W. (2022, December). Gamifying Experiential Learning Theory. Presented at International Conference On Web-Based Learning (ICWL 2022), Tenerife, Spain

GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images (2022)
Presentation / Conference Contribution
Talon, D., Del Bue, A., & James, S. (2022, October). GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images. Presented at IEEE International Conference on Image Processing, Bordeaux, France

Puzzle solving is a combinatorial challenge due to the difficulty of matching adjacent pieces. Instead, we infer a mental image from all pieces, which a given piece can then be matched against avoiding the combinatorial explosion. Exploiting advancem... Read More about GANzzle: Reframing jigsaw puzzle solving as a retrieval task using generative mental images.

Multi-modal lung ultrasound image classification by fusing image-based features and probe information (2022)
Presentation / Conference Contribution
Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2022, November). Multi-modal lung ultrasound image classification by fusing image-based features and probe information. Presented at IEEE International Conference on BioInformatics and BioEngineering (BIBE 2022), Taichung, Taiwan

Lung ultrasound is a widely used portable, cheap, and non-invasive medical imaging technology that can be used to identify various lung pathologies. In this work, we propose a multi-modal approach for lung ultrasound image classification that combine... Read More about Multi-modal lung ultrasound image classification by fusing image-based features and probe information.

Finding matching cuts in H-free graphs (2022)
Presentation / Conference Contribution
Lucke, F., Paulusma, D., & Ries, B. (2021, December). Finding matching cuts in H-free graphs. Presented at 33rd International Symposium on Algorithms and Computation (ISAAC 2022), Seoul, South Korea

The well-known NP-complete problem Matching Cut is to decide if a graph has a matching that is also an edge cut of the graph. We prove new complexity results for Matching Cut restricted to H-free graphs, that is, graphs that do not contain some fixed... Read More about Finding matching cuts in H-free graphs.