8 citations · 11 across the 11 of their papers we have counts for
15 papers
SynthGait-19K: A Physically Grounded Synthetic Video Dataset for Gait Parameter Estimation
Soroush Mehraban, Xin Lei Lin, Vida Adeli +5
Accurate estimation of clinically meaningful gait parameters from monocular video is important for scalable mobility assessment, yet progress is limited by the small scale, restric…
Evaluation Protocols and Validation for Cameras in Indoor Healthcare Monitoring
Amirhossein Dadashzadeh, Jingjing Liu, Qianhui Men +5
Camera-based monitoring systems are increasingly adopted in healthcare settings for the continuous assessment of patient movement and activities. However, their technical performan…
Probability-Conserving Flow Guidance
Parsa Esmati, Junha Hyung, Amirhossein Dadashzadeh +2
Diffusion and flow-based generative models dominate visual synthesis, with guidance aligning samples to user input and improving perceptual quality. However, Classifier-Free Guidan…
CARE-PD: A Multi-Site Anonymized Clinical Dataset for Parkinson's Disease Gait Assessment
Vida Adeli, Ivan Klabucar, Javad Rajabi +25
Objective gait assessment in Parkinson's Disease (PD) is limited by the absence of large, diverse, and clinically annotated motion datasets. We introduce CARE-PD, the largest publi…
Trajectory-guided Motion Perception for Facial Expression Quality Assessment in Neurological Disorders
Shuchao Duan, Amirhossein Dadashzadeh, Alan Whone +1
Automated facial expression quality assessment (FEQA) in neurological disorders is critical for enhancing diagnostic accuracy and improving patient care, yet effectively capturing…
Unsupervised Cross-Domain 3D Human Pose Estimation via Pseudo-Label-Guided Global Transforms
Jingjing Liu, Zhiyong Wang, Xinyu Fan +3
Existing 3D human pose estimation methods often suffer in performance, when applied to cross-scenario inference, due to domain shifts in characteristics such as camera viewpoint, p…
Co-STAR: Collaborative Curriculum Self-Training with Adaptive Regularization for Source-Free Video Domain Adaptation
Amirhossein Dadashzadeh, Parsa Esmati, Majid Mirmehdi
Recent advances in Source-Free Unsupervised Video Domain Adaptation (SFUVDA) leverage vision-language models to enhance pseudo-label generation. However, challenges such as noisy p…
GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domain
Vida Adeli, Soroush Mehraban, Majid Mirmehdi +6
Gait analysis is crucial for the diagnosis and monitoring of movement disorders like Parkinson's Disease. While computer vision models have shown potential for objectively evaluati…
SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers
Parsa Esmati, Amirhossein Dadashzadeh, Vahid Goodarzi +2
Current approaches using sequential networks have shown promise in estimating field variables for dynamical systems, but they are often limited by high rollout errors. The unresolv…
QAFE-Net: Quality Assessment of Facial Expressions with Landmark Heatmaps
Shuchao Duan, Amirhossein Dadashzadeh, Alan Whone +1
Facial expression recognition (FER) methods have made great inroads in categorising moods and feelings in humans. Beyond FER, pain estimation methods assess levels of intensity in…
PECoP: Parameter Efficient Continual Pretraining for Action Quality Assessment
Amirhossein Dadashzadeh, Shuchao Duan, Alan Whone +1
The limited availability of labelled data in Action Quality Assessment (AQA), has forced previous works to fine-tune their models pretrained on large-scale domain-general datasets.…
Auxiliary Learning for Self-Supervised Video Representation via Similarity-based Knowledge Distillation
Amirhossein Dadashzadeh, Alan Whone, Majid Mirmehdi
Despite the outstanding success of self-supervised pretraining methods for video representation learning, they generalise poorly when the unlabeled dataset for pretraining is small…
Exploring Motion Boundaries in an End-to-End Network for Vision-based Parkinson's Severity Assessment
Amirhossein Dadashzadeh, Alan Whone, Michal Rolinski +1
Evaluating neurological disorders such as Parkinson's disease (PD) is a challenging task that requires the assessment of several motor and non-motor functions. In this paper, we pr…
Multi-Level Contextual Network for Biomedical Image Segmentation
Amirhossein Dadashzadeh, Alireza Tavakoli Targhi
Accurate and reliable image segmentation is an essential part of biomedical image analysis. In this paper, we consider the problem of biomedical image segmentation using deep convo…
HGR-Net: A Fusion Network for Hand Gesture Segmentation and Recognition
Amirhossein Dadashzadeh, Alireza Tavakoli Targhi, Maryam Tahmasbi +1
We propose a two-stage convolutional neural network (CNN) architecture for robust recognition of hand gestures, called HGR-Net, where the first stage performs accurate semantic seg…