  This paper presents a novel mid-wave infrared (MWIR) small target detection
dataset (MWIRSTD) comprising 14 video sequences containing approximately 1053
images with annotated targets of three distinct classes of small objects.
Captured using cooled MWIR imagers, the dataset offers a unique opportunity for
researchers to develop and evaluate state-of-the-art methods for small object
detection in realistic MWIR scenes. Unlike existing datasets, which primarily
consist of uncooled thermal images or synthetic data with targets superimposed
onto the background or vice versa, MWIRSTD provides authentic MWIR data with
diverse targets and environments. Extensive experiments on various traditional
methods and deep learning-based techniques for small target detection are
performed on the proposed dataset, providing valuable insights into their
efficacy. The dataset and code are available at
https://github.com/avinres/MWIRSTD.
