Effective detection of bus passengers enhances the intelligence and automation of public transportation systems, but it is challenged by complex backgrounds and severe scale imbalances. To address these challenges, we introduce DAEAR-DETR, a novel neural network architecture employing Dual-Attention mechanisms and Echo Accumulative Residuals (EAR) for bus passenger detection. This model features a Dual-Attention Encoder comprising the Low-Level Local Attention Module (LLLAM) and the High-Level Global Attention Module (HLGAM). Additionally, it integrates a Bidirectional Cross-scale Feature-Fusi...
