  Small target motion detection is critical for insects to search for and track
mates or prey which always appear as small dim speckles in the visual field. A
class of specific neurons, called small target motion detectors (STMDs), has
been characterized by exquisite sensitivity for small target motion.
Understanding and analyzing visual pathway of STMD neurons are beneficial to
design artificial visual systems for small target motion detection. Feedback
loops have been widely identified in visual neural circuits and play an
important role in target detection. However, if there exists a feedback loop in
the STMD visual pathway or if a feedback loop could significantly improve the
detection performance of STMD neurons, is unclear. In this paper, we propose a
feedback neural network for small target motion detection against naturally
cluttered backgrounds. In order to form a feedback loop, model output is
temporally delayed and relayed to previous neural layer as feedback signal.
Extensive experiments showed that the significant improvement of the proposed
feedback neural network over the existing STMD-based models for small target
motion detection.
