Underwater RGB–sonar object detection remains challenging due to severe optical degradation, strong sonar noise, and spatial misalignment between heterogeneous modalities. Existing multimodal detectors usually rely on simple feature aggregation or limited structural coupling, which cannot effectively model global cross-modal dependencies or address modality-specific degradation. To address these challenges, we propose Chrs-Net...