1 citations
3 papers
cs.CV2026★ 1 cited
Impact Detection in Fall Events: Leveraging Spatio-Temporal Graph Convolutional Networks and Recurrent Neural Networks Using 3D Skeletons Data
Tresor Y. Koffi, Youssef Mourchid, Mohammed Hindawi +1
Fall represents a significant risk of accidental death among individuals aged over 65, presenting a global health concern. A fall is defined as any event where a person loses balan…
cs.CV2026★ 1 cited
DistillH-Mamba: A Hypergraph-Mamba-Based Knowledge Distillation Model for Efficient Impact Fall Detection
Tresor Y. Koffi, Youssef Mourchid, Mohammed Hindawi +1
Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning has improved fall detection, a…
cs.CV2026
Kinetic Mining in Context: Few-Shot Action Synthesis via Text-to-Motion Distillation
Luca Cazzola, Ahed Alboody
The acquisition cost for large, annotated motion datasets remains a critical bottleneck for skeletal-based Human Activity Recognition (HAR). Although Text-to-Motion (T2M) generativ…