RoPE-T: Rotary Position Embedding for Enhanced Temporal Modeling in Video-Based Human Action Recognition
Human action recognition requires modeling both spatial information and temporal relationships across video frames. While Transformer encoders are effective for capturing long-range dependencies, standard self-attention mechanisms do not inherently encode the sequential order of input tokens. To address this limitation...