# Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection

Source: [Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection](<https://www.sota2.com/research/paper/6a0fe33df984739ed6739fcd>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-05-23T05:00:11.413Z

Authors: Liuyang Wang, Feitian Zhang

Published: 2026-05-21T15:18:34.000Z

## Abstract

Object detection from Unmanned Aerial Vehicles (UAVs) is challenged by severe ego-motion, camera jitter, and large scale variations. While modern detectors perform well on static images, their direct application to UAV video often fails, particularly for small objects in dynamic scenes. Existing motion-based methods either rely on computationally expensive optical flow or use single-interval differencing, which is sensitive to jitter and limited in capturing diverse motion patterns. We propose a vision-only motion-guided detection framework that decouples target motion from camera-induced disturbances. A homography-based Global Motion Compensation (GMC) first aligns adjacent frames. We then introduce a Dual-Interval Motion Extraction strategy that captures both short-term and long-term motion cues. To integrate these cues, a lightweight Motion-Guided Attention (MGA) module enhances feature representations within a Feature Pyramid Network. Experiments on the VisDrone-VID dataset demonstrate consistent improvements over a strong YOLOv8 baseline under severe ego-motion. Ablation studies further confirm the effectiveness of the dual-interval design and the proposed motion-guided attention mechanism.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Object Detection on VisDrone-VID (val)](<https://www.sota2.com/research/sota/object-detection-on-visdrone-vid-val.md>): Object Detection; VisDrone-VID (val); mAP@0.5: 27.4.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2605.22605>)

[PDF](<https://arxiv.org/pdf/2605.22605.pdf>)