13 citations · 24 across the 35 of their papers we have counts for
23 papers · 1 filter
Sparse Multi-Stage Expert-Agent Routing for Complex Clinical Reasoning
Sike Xiang, Shuang Chen, Qian sun +3
Complex clinical reasoning requires models to update diagnostic hypotheses as new evidence emerges and to coordinate different medical specialities under limited consultation resou…
HSTGFormer: Hyper Spatial-Temporal Graph Transformer for 3D Human Pose Estimation
Ruochen Li, Shuang Chen, Wenke E +2
Transformer-based methods have achieved strong performance in monocular 3D human pose estimation, but most existing approaches organise spatial and temporal reasoning as separate s…
RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization
Yan Lin, Ziheng Wang, Shuang Chen +2
Medical image classifiers are often trained within one source population, yet clinical deployment requires robustness to patients whose appearance, acquisition style, and disease p…
UIESNN: A Scale-Aware Spiking Network for Underwater Image Enhancement
Shuang Chen, Ruochen Li, Zihan Zhu +3
Underwater image enhancement (UIE) is a practically important yet underexplored application of spiking neural networks (SNNs), where the dominant degradations are large-scale and l…
Missingness-Conditioned Spatio-Temporal Fusion for Human Activity Recognition from Low-Quality Wearable Sensor Data
Jiangtao Fan, Anish Jindal, Amir Atapour-Abarghouei
Body-worn sensor networks capture human activities through complementary views, where nodes, modalities, and axes partially describe the underlying motion. In real deployments, har…
Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving
Ghadah Alosaimi, Hanadi Alhamdan, Wenke E +3
Predicting driver intention from neurophysiological signals offers a promising pathway for enhancing proactive safety in advanced driver assistance systems, yet remains challenging…
Motion-Adaptive Multi-Scale Temporal Modelling with Skeleton-Constrained Spatial Graphs for Efficient 3D Human Pose Estimation
Ruochen Li, Shuang Chen, Wenke E +2
Accurate 3D human pose estimation from monocular videos requires effective modelling of complex spatial and temporal dependencies. However, existing methods often face challenges i…
ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations
Ruochen Li, Ziyi Chang, Junyan Hu +3
Accurate prediction of real-world pedestrian trajectories is crucial for a wide range of robot-related applications. Recent approaches typically adopt graph-based or transformer-ba…
Exploring the Potentials of Spiking Neural Networks for Image Deraining
Shuang Chen, Tomas Krajnik, Farshad Arvin +1
Biologically plausible and energy-efficient frameworks such as Spiking Neural Networks (SNNs) have not been sufficiently explored in low-level vision tasks. Taking image deraining…
KD360-VoxelBEV: LiDAR and 360-degree Camera Cross Modality Knowledge Distillation for Bird's-Eye-View Segmentation
Wenke E, Yixin Sun, Jiaxu Liu +3
We present the first cross-modality distillation framework specifically tailored for single-panoramic-camera Bird's-Eye-View (BEV) segmentation. Our approach leverages a novel LiDA…
CaFlow: Enhancing Long-Term Action Quality Assessment with Causal Counterfactual Flow
Ruisheng Han, Kanglei Zhou, Shuang Chen +2
Action Quality Assessment (AQA) predicts fine-grained execution scores from action videos and is widely applied in sports, rehabilitation, and skill evaluation. Long-term AQA, as i…
BcQLM: Efficient Vision-Language Understanding with Distilled Q-Gated Cross-Modal Fusion
Sike Xiang, Shuang Chen, Amir Atapour-Abarghouei
As multimodal large language models (MLLMs) advance, their large-scale architectures pose challenges for deployment in resource-constrained environments. In the age of large models…
DEEP-SEA: Deep-Learning Enhancement for Environmental Perception in Submerged Aquatics
Shuang Chen, Ronald Thenius, Farshad Arvin +1
Continuous and reliable underwater monitoring is essential for assessing marine biodiversity, detecting ecological changes and supporting autonomous exploration in aquatic environm…
FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment
Ruisheng Han, Kanglei Zhou, Amir Atapour-Abarghouei +2
Action quality assessment (AQA) is critical for evaluating athletic performance, informing training strategies, and ensuring safety in competitive sports. However, existing deep le…
Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving
Wenke E, Chao Yuan, Li Li +4
We present Dur360BEV, a novel spherical camera autonomous driving dataset equipped with a high-resolution 128-channel 3D LiDAR and a RTK-refined GNSS/INS system, along with a bench…
SEM-Net: Efficient Pixel Modelling for image inpainting with Spatially Enhanced SSM
Shuang Chen, Haozheng Zhang, Amir Atapour-Abarghouei +1
Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. \revise{Achieving semantically plausible inpainting results is…
MxT: Mamba x Transformer for Image Inpainting
Shuang Chen, Amir Atapour-Abarghouei, Haozheng Zhang +1
Image inpainting, or image completion, is a crucial task in computer vision that aims to restore missing or damaged regions of images with semantically coherent content. This techn…
HINT: High-quality INPainting Transformer with Mask-Aware Encoding and Enhanced Attention
Shuang Chen, Amir Atapour-Abarghouei, Hubert P. H. Shum
Existing image inpainting methods leverage convolution-based downsampling approaches to reduce spatial dimensions. This may result in information loss from corrupted images where t…
INCLG: Inpainting for Non-Cleft Lip Generation with a Multi-Task Image Processing Network
Shuang Chen, Amir Atapour-Abarghouei, Edmond S. L. Ho +1
We present a software that predicts non-cleft facial images for patients with cleft lip, thereby facilitating the understanding, awareness and discussion of cleft lip surgeries. To…
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets
Michael Luke Battle, Amir Atapour-Abarghouei, Andrew Stephen McGough
Skin cancer is the most common malignancy in the world. Automated skin cancer detection would significantly improve early detection rates and prevent deaths. To help with this aim,…
A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip
Shuang Chen, Amir Atapour-Abarghouei, Jane Kerby +4
A Cleft lip is a congenital abnormality requiring surgical repair by a specialist. The surgeon must have extensive experience and theoretical knowledge to perform surgery, and Arti…
"Just Drive": Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving
Jack Stelling, Amir Atapour-Abarghouei
Biases can filter into AI technology without our knowledge. Oftentimes, seminal deep learning networks champion increased accuracy above all else. In this paper, we attempt to alle…
Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification
Peter J. Bevan, Amir Atapour-Abarghouei
Convolutional Neural Networks have demonstrated dermatologist-level performance in the classification of melanoma from skin lesion images, but prediction irregularities due to bias…