  Single-frame infrared small target detection remains a challenge not only due
to the scarcity of intrinsic target characteristics but also because of lacking
a public dataset. In this paper, we first contribute an open dataset with
high-quality annotations to advance the research in this field. We also propose
an asymmetric contextual modulation module specially designed for detecting
infrared small targets. To better highlight small targets, besides a top-down
global contextual feedback, we supplement a bottom-up modulation pathway based
on point-wise channel attention for exchanging high-level semantics and subtle
low-level details. We report ablation studies and comparisons to
state-of-the-art methods, where we find that our approach performs
significantly better. Our dataset and code are available online.
