Abstract: Multispectral object detection technology is an approach that utilizes information derived from diverse wavelength spectra to detect and recognize objects. This technology integrates data of different spectras from visible light, infrared, and thermal imaging, and improves the accuracy and robustness of object detection. This technology performs excellently in low-light or other challenging environments. This technology is commonly applied in fields such as night vision monitoring, meteorological observation, agriculture, and environmental monitoring. First, the definition, acquisition methods, and common datasets of multispectral images are explained. Second, multispectral object detection algorithms are categorized, and examples of relevant algorithms are given. Third, the applications of the algorithms, which center on specific application cases in pedestrian detection, agriculture, and environmental monitoring, are discussed. Finally, the future directions for multispectral object detection are explored.