CLSC DETR: Reliable Candidate Ranking via Cross Layer Geometric Support for UAV Small Object Detection
Unmanned aerial vehicle (UAV) object detection is critical for applications such as target search, where accurate detection of small objects in complex aerial scenes remains challenging. The limited spatial extent, dense distribution, and frequent occlusion of small objects make reliable candidate ranking particularly difficult. Existing Detection Transformer (DETR) based methods improve ranking by estimating localization quality from individual queries and incorporating it into classification scores. However, a single query often lacks sufficient geometric evidence for small objects with weak boundary cues, resulting in unreliable quality estimation and unstable ranking. To address this ...
| Authors | Junyan Lin |
|---|---|
| Primary category | cs.CV |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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