Dynamic Spatial-Temporal Aggregation for Skeleton-Aware Sign Language Recognition

arXiv:2403.12519v1 Announce Type: new
Abstract: Skeleton-aware sign language recognition (SLR) has gained popularity due to its ability to remain unaffected by background information and its lower computational requirements. Current methods utilize spatial graph modules and temporal modules to capture spatial and temporal features, respectively. However, their spatial graph modules are typically built on fixed graph structures such as graph convolutional networks or a single learnable graph, which only partially explore joint relationships. Additionally, a simple temporal convolution kernel is used …

aggregation arxiv cs.cv dynamic language recognition spatial temporal type