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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 81–90 of 107 papers

TitleStatusHype
Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss—0
Few Could Be Better Than All: Feature Sampling and Grouping for Scene Text Detection—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Sampling Equivariant Self-attention Networks for Object Detection in Aerial Images—0
Gliding vertex on the horizontal bounding box for multi-oriented object detection—0
Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery—0
IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection—0
Investigating the Challenges of Class Imbalance and Scale Variation in Object Detection in Aerial Images—0
Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images—0
Rotated Object Detection via Scale-invariant Mahalanobis Distance in Aerial Images—0
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