UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery
Robotics Research (United States)
Abstract
Unmanned aerial vehicle object detection (UAV-OD) has been widely used in various scenarios. However, most existing UAV-OD algorithms rely on manually designed components, which require extensive tuning. End-to-end models that do not depend on such manually designed components are mainly designed for natural images, which are less effective for UAV imagery. To address such challenges, this paper proposes an efficient detection transformer (DETR) framework tailored for UAV imagery, i.e., UAV-DETR. The framework includes a multi-scale feature fusion with frequency enhancement module, which captures both spatial and frequency information at different scales. In addition, a frequency-focused downsampling module is…
Citation impact
- FWCI
- 46.09
- Percentile
- 100%
- References
- 26
Authors
5Topics & keywords
- Object detection
- Upsampling
- Fuse (electrical)
- Aerial imagery
- Aerial image
- Sensor fusion
- Object (grammar)
- Feature extraction