# Space Object Detection using Multi-frame Temporal Trajectory Completion Method

arXiv: https://arxiv.org/abs/2510.19220 · HTML: https://mlsanity.com/paper/2510.19220/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 27 references that are in the map.
- First posted on arXiv 22 Oct 2025.

## Builds on (most cited first, 7 of 7)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [YOLOv11: An Overview of the Key Architectural Enhancements](https://mlsanity.com/paper/2410.17725/) (2024)
- [Dense Nested Attention Network for Infrared Small Target Detection](https://mlsanity.com/paper/2106.00487/) (2021)
- [HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection](https://mlsanity.com/paper/2403.10778/) (2024)
- [SpirDet: Towards Efficient, Accurate and Lightweight Infrared Small Target Detector](https://mlsanity.com/paper/2402.05410/) (2024)
- [Topological Sweep for Multi-Target Detection of Geostationary Space Objects](https://mlsanity.com/paper/2003.09583/) (2020)
- [High Performance Space Debris Tracking in Complex Skylight Backgrounds with a Large-Scale Dataset](https://mlsanity.com/paper/2506.02614/) (2025)

## Abstract (arXiv)

Space objects in Geostationary Earth Orbit (GEO) present significant detection challenges in optical imaging due to weak signals, complex stellar backgrounds, and environmental interference. In this paper, we enhance high-frequency features of GEO targets while suppressing background noise at the single-frame level through wavelet transform. Building on this, we propose a multi-frame temporal trajectory completion scheme centered on the Hungarian algorithm for globally optimal cross-frame matching. To effectively mitigate missing and false detections, a series of key steps including temporal matching and interpolation completion, temporal-consistency-based noise filtering, and progressive trajectory refinement are designed in the post-processing pipeline. Experimental results on the public SpotGEO dataset demonstrate the effectiveness of the proposed method, achieving an F_1 score of 90.14%.