# A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds

arXiv: https://arxiv.org/abs/1801.06687 · HTML: https://mlsanity.com/paper/1801.06687/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2018.

## Built on by (most cited first, 6 of 6)

- [Attention and Prediction Guided Motion Detection for Low-Contrast Small Moving Targets](https://mlsanity.com/paper/2104.13018/) (2021)
- [vSTMD: Visual Motion Detection for Extremely Tiny Target at Various Velocities](https://mlsanity.com/paper/2501.13054/) (2025)
- [A Bioinspired Retinal Neural Network for Accurately Extracting Small-Target Motion Information in Cluttered Backgrounds](https://mlsanity.com/paper/2103.00848/) (2021)
- [Spatio-Temporal Feedback Control of Small Target Motion Detection Visual System](https://mlsanity.com/paper/2211.10128/) (2022)
- [TSOM: Small Object Motion Detection Neural Network Inspired by Avian Visual Circuit](https://mlsanity.com/paper/2404.00855/) (2024)
- [MITE-Net: SWaP-Optimized 4K Video Tiny Target Perception for Embodied Edge SAR](https://mlsanity.com/paper/2608.15830/) (2026)

## Abstract (arXiv)

Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the fly's visual system, a class of specific neurons, called small target motion detectors (STMDs), have been identified as showing exquisite selectivity for small target motion. Some of the STMDs have also demonstrated directional selectivity which means these STMDs respond strongly only to their preferred motion direction. Directional selectivity is an important property of these STMD neurons which could contribute to tracking small targets such as mates in flight. However, little has been done on systematically modeling these directional selective STMD neurons. In this paper, we propose a directional selective STMD-based neural network (DSTMD) for small target detection in a cluttered background. In the proposed neural network, a new correlation mechanism is introduced for direction selectivity via correlating signals relayed from two pixels. Then, a lateral inhibition mechanism is implemented on the spatial field for size selectivity of STMD neurons. Extensive experiments showed that the proposed neural network not only is in accord with current biological findings, i.e. showing directional preferences, but also worked reliably in detecting small targets against cluttered backgrounds.