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All Outputs (1379)

Towards Open-World Object-Based Anomaly Detection viaSelf-Supervised Outlier Synthesis (2024)
Presentation / Conference Contribution
Isaac-Medina, B., Gaus, Y., Bhowmik, N., & Breckon, T. (2024, September). Towards Open-World Object-Based Anomaly Detection viaSelf-Supervised Outlier Synthesis. Presented at ECCV 2024: European Conference on Computer Vision, Milan, Italy

Object detection is a pivotal task in computer vision that has received significant attention in previous years. Nonetheless, the capability of a detector to localise objects out of the training distribution remains unexplored. Whilst recent approach... Read More about Towards Open-World Object-Based Anomaly Detection viaSelf-Supervised Outlier Synthesis.

MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment (2024)
Presentation / Conference Contribution
Zhou, K., Wang, L., Zhang, X., Shum, H. P. H., Li, F. W. B., Li, J., & Liang, X. (2024, September). MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment. Presented at ECCV 2024: The 18th European Conference on Computer Vision, Milan, Italy

Action Quality Assessment (AQA) evaluates diverse skills but models struggle with non-stationary data. We propose Continual AQA (CAQA) to refine models using sparse new data. Feature replay preserves memory without storing raw inputs. However, the mi... Read More about MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment.

Declarative Lifecycle Management in Digital Twins (2024)
Presentation / Conference Contribution
Bencomo, N., Kamburjan, E., Tapia Tarifa, S. L., & Broch-Johnsen, E. (2024, September). Declarative Lifecycle Management in Digital Twins. Presented at 1st International Conference on Engineering Digital Twins (EDTconf 2024), Linz, Austria

Together, a digital twin and its physical counterpart can be seen as a self-adaptive system: the digital twin monitors the physical system, updates its own internal model of the physical system, and adjusts the physical system by means of controllers... Read More about Declarative Lifecycle Management in Digital Twins.

Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning (2024)
Presentation / Conference Contribution
Champagnie, K., Chen, B., Arvin, F., & Hu, J. (2024, August). Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning. Presented at 2024 IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy

Two promising approaches to coverage path planning are reward-based and pheromone-based methods. Reward-based methods allow heuristics to be learned automatically, often yielding a superior performance to hand-crafted rules. On the other hand, pherom... Read More about Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning.

A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments (2024)
Presentation / Conference Contribution
Sun, H., Hu, J., Dai, L., & Chen, B. (2024, August). A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments. Presented at 2024 IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy

Safety-guaranteed trajectories are important for multi-agent systems to work in an unknown constrained environment. To address this issue, this paper proposes a cooperative path planning strategy for a swarm of agents such that they can achieve a tar... Read More about A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments.

Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education (2024)
Presentation / Conference Contribution
Liu, J., Law, L.-C., & Shum, H. P. H. (2024, October). Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education. Presented at NordiCHI 2024, Uppsala

Driven by the recent incorporation of chatbots into art education, art critique as a key factor in this realm poses distinct challenges and opportunities for this technology intervention. This study investigates the efficacy of chatbot-generated crit... Read More about Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education.

Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education (2024)
Presentation / Conference Contribution
Liu, J., Law, E. L.-C., & Shum, H. P. H. (2024, October). Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education. Presented at NordiCHI 2024: Nordic Conference on Human-Computer Interaction, Uppsala Sweden

Driven by the recent incorporation of chatbots into art education, art critique as a key factor in this realm poses distinct challenges and opportunities for this technology intervention. This study investigates the efficacy of chatbot-generated crit... Read More about Chatbots and Art Critique: A Comparative Study of Chatbot and Human Experts in Traditional Chinese Painting Education.

RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems (2024)
Presentation / Conference Contribution
Agachi, C., Arvin, F., & Hu, J. (2024, August). RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems. Presented at 2024 IEEE International Conference on Intelligent Systems (IS), Varna, Bulgaria

Coordination of multi-agent systems has received significant attention during the past few years owing to its wide real-world applications, such as cooperative exploration, aircraft formation, and autonomous vehicle platooning. To address this issue,... Read More about RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems.

Integrating Speech Input in Educational Immersive Virtual Reality Applications: A Systematic Review (2024)
Presentation / Conference Contribution
Alghamdi, N., & Cristea, A. I. (2024, August). Integrating Speech Input in Educational Immersive Virtual Reality Applications: A Systematic Review. Presented at 2024 IEEE 12th International Conference on Intelligent Systems (IS), Varna, Bulgaria

The topic of immersive virtual reality (IVR) in education has gained increasing attention in recent years, due to its potential to enhance learner outcomes and to mitigate learning costs. As we can capture a multitude of information from speech and g... Read More about Integrating Speech Input in Educational Immersive Virtual Reality Applications: A Systematic Review.

RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation (2024)
Presentation / Conference Contribution
Li, L., Shum, H. P. H., & Breckon, T. P. (2024, September). RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation. Presented at ECCV 2024: European Conference on Computer Vision, Milan, Italy

3D point clouds play a pivotal role in outdoor scene perception, especially in the context of autonomous driving. Recent advancements in 3D LiDAR segmentation often focus intensely on the spatial positioning and distribution of points for accurate se... Read More about RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation.

Two-Person Interaction Augmentation with Skeleton Priors (2024)
Presentation / Conference Contribution
Li, B., Ho, E. S. L., Shum, H. P. H., & Wang, H. (2024, June). Two-Person Interaction Augmentation with Skeleton Priors. Presented at 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, Washington

Close and continuous interaction with rich contacts is a crucial aspect of human activities (e.g. hugging, dancing) and of interest in many domains like activity recognition, motion prediction, character animation, etc. However, acquiring such skelet... Read More about Two-Person Interaction Augmentation with Skeleton Priors.

ArtAI4DS: AI Art and Its Empowering Role in Digital Storytelling (2024)
Presentation / Conference Contribution
Fernandes, T., Nisi, V., Nunes, N., & James, S. (2024, September). ArtAI4DS: AI Art and Its Empowering Role in Digital Storytelling. Presented at IFIP International Conference on Entertainment Computing, Manaus, Brazil

In an era of global interconnections, storytelling is a compelling medium for fostering understanding, building connections, and facilitating cultural exchange. Throughout history, visual imagery has been used to enrich narratives. However, this has... Read More about ArtAI4DS: AI Art and Its Empowering Role in Digital Storytelling.

Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving (2024)
Presentation / Conference Contribution
Tsesmelis, T., Palmieri, L., Khoroshiltseva, M., Islam, A., Elkin, G., Itzhak Shahar, O., Scarpellini, G., Fiorini, S., Ohayon, Y., Alali, N., Aslan, S., Morerio, P., Vascon, S., gravina, E., Cristina Napolitano, M., Scarpati, G., zuchtriegel, G., Spühler, A., Fuchs, M. E., James, S., …Del Bue, A. (2024, December). Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving. Presented at Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, Vancouver, Canada

This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for... Read More about Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving.

Towards Communication-Efficient Peer-to-Peer Networks (2024)
Presentation / Conference Contribution
Hourani, K., Moses Jr., W. K., & Pandurangan, G. (2024, September). Towards Communication-Efficient Peer-to-Peer Networks. Presented at 32nd Annual European Symposium on Algorithms (ESA 2024), Egham, United Kingdom

We focus on designing Peer-to-Peer (P2P) networks that enable efficient communication. Over the last two decades, there has been substantial algorithmic research on distributed protocols for building P2P networks with various desirable properties suc... Read More about Towards Communication-Efficient Peer-to-Peer Networks.

Scheduling with Obligatory Tests (2024)
Presentation / Conference Contribution
Dogeas, K., Erlebach, T., & Liang, Y.-C. (2024, September). Scheduling with Obligatory Tests. Presented at 32nd Annual European Symposium on Algorithms (ESA 2024), Egham, United Kingdom

Motivated by settings such as medical treatments or aircraft maintenance, we consider a scheduling problem with jobs that consist of two operations, a test and a processing part. The time required to execute the test is known in advance while the tim... Read More about Scheduling with Obligatory Tests.

Detrimental task execution patterns in mainstream OpenMP runtimes (2024)
Presentation / Conference Contribution
Weinzierl, T., Tuft, A., & Klemm, M. (2024, September). Detrimental task execution patterns in mainstream OpenMP runtimes. Presented at IWOMP 2024, Perth, Australia

The OpenMP API offers both task-based and data-parallel concepts to scientific computing. While it provides descriptive and prescriptive annotations, it is in many places deliberately unspecific how to implement its annotations. As the predomina... Read More about Detrimental task execution patterns in mainstream OpenMP runtimes.

Competitive Query Minimization for Stable Matching with One-Sided Uncertainty (2024)
Presentation / Conference Contribution
Bampis, E., Dogeas, K., Erlebach, T., Megow, N., Schlöter, J., & Trehan, A. (2024, August). Competitive Query Minimization for Stable Matching with One-Sided Uncertainty. Presented at International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2024), London, UK

We study the two-sided stable matching problem with one-sided uncertainty for two sets of agents A and B, with equal cardinality. Initially, the preference lists of the agents in A are given but the preferences of the agents in B are unknown. An algo... Read More about Competitive Query Minimization for Stable Matching with One-Sided Uncertainty.