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Object Detection In Aerial Images

Object Detection in Aerial Images is the task of detecting objects from aerial images.

( Image credit: DOTA: A Large-Scale Dataset for Object Detection in Aerial Images )

Papers

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Showing 26–50 of 107 papers

TitleStatusHype
DARDet: A Dense Anchor-free Rotated Object Detector in Aerial ImagesCode1
PIoU Loss: Towards Accurate Oriented Object Detection in Complex EnvironmentsCode1
HA-RDet: Hybrid Anchor Rotation Detector for Oriented Object DetectionCode1
Oriented RepPoints for Aerial Object DetectionCode1
Density Map Guided Object Detection in Aerial ImagesCode1
Oriented Object Detection in Aerial Images with Box Boundary-Aware VectorsCode1
Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher LearningCode1
Oriented R-CNN for Object DetectionCode1
SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated ObjectsCode1
Beyond Bounding-Box: Convex-Hull Feature Adaptation for Oriented and Densely Packed Object DetectionCode1
Enhancing Fine-grained Object Detection in Aerial Images via Orthogonal MappingCode1
A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object DetectionCode1
Dynamic Refinement Network for Oriented and Densely Packed Object DetectionCode1
Learning RoI Transformer for Oriented Object Detection in Aerial ImagesCode1
FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite ImageryCode1
Align Deep Features for Oriented Object DetectionCode1
Optimization for Arbitrary-Oriented Object Detection via Representation Invariance LossCode1
Object Detection in Aerial Images: A Large-Scale Benchmark and ChallengesCode1
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing ImagesCode1
CLIP-Guided Source-Free Object Detection in Aerial ImagesCode1
LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial ImageryCode1
Dynamic Anchor Learning for Arbitrary-Oriented Object DetectionCode1
Learning to Reduce Information Bottleneck for Object Detection in Aerial ImagesCode1
DOTA: A Large-scale Dataset for Object Detection in Aerial ImagesCode1
Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkCode1
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