Multispectral Object Detection

Multispectral object detection is an important branch in the field of computer vision, aiming to improve the accuracy and reliability of outdoor scene analysis by combining data from the visible spectrum with non-visible spectra (such as infrared). This technology can effectively address challenges like insufficient lighting and adverse weather conditions, enhancing the robustness of object recognition. Although deep learning has demonstrated significant potential in multispectral scene analysis, many open research questions remain, and it has not been widely deployed in the industry. The goal of multispectral object detection is to develop efficient and reliable algorithms to achieve precise object recognition in complex environments, which holds important application value.