7 papers
Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis
Guangyu Sun, Wenhan Wu, Zhishuai Guo +3
Automated recognition of autistic behaviors in children is essential for early intervention and objective clinical assessment. However, the development of robust models is severely…
Monocular Models are Strong Learners for Multi-View Human Mesh Recovery
Haoyu Xie, Shengkai Xu, Cheng Guo +6
Multi-view human mesh recovery (HMR) is broadly deployed in diverse domains where high accuracy and strong generalization are essential. Existing approaches can be broadly grouped…
KHMP: Frequency-Domain Kalman Refinement for High-Fidelity Human Motion Prediction
Wenhan Wu, Zhishuai Guo, Chen Chen +4
Stochastic human motion prediction aims to generate diverse, plausible futures from observed sequences. Despite advances in generative modeling, existing methods often produce pred…
Communication-Efficient Federated AUC Maximization with Cyclic Client Participation
Umesh Vangapally, Wenhan Wu, Chen Chen +1
Federated AUC maximization is a powerful approach for learning from imbalanced data in federated learning (FL). However, existing methods typically assume full client availability,…
UniSTFormer: Unified Spatio-Temporal Lightweight Transformer for Efficient Skeleton-Based Action Recognition
Wenhan Wu, Zhishuai Guo, Chen Chen +1
Skeleton-based action recognition (SAR) has achieved impressive progress with transformer architectures. However, existing methods often rely on complex module compositions and hea…
Frequency-Semantic Enhanced Variational Autoencoder for Zero-Shot Skeleton-based Action Recognition
Wenhan Wu, Zhishuai Guo, Chen Chen +2
Zero-shot skeleton-based action recognition aims to develop models capable of identifying actions beyond the categories encountered during training. Previous approaches have primar…