TSPNet: Temporal-Spatial Pyramid Network for Infrared Maritime Object Detection

Infrared object detection is one of the critical technologies for maritime search and rescue. However, it is still challenging due to the strong background clutter interference and the lack of small object information. We proposed a temporal-spatial pyramid network for infrared maritime object detection. We proposed a nested temporal pyramid to represent the temporal features through motion differences maps and energy accumulation maps to distinguish the wave clutter and objects. We proposed a dense spatial pyramid to learn the spatial features and the differences between temporal maps and then to clarify and locate objects. For training, we designed a scale-related composite loss function with correlated location description and weighted confidence loss. Finally, based on the ablation and comparison experiments, the proposed method performs better on maritime infrared sequences.