Pointwise Frequency Attention and Coarse-to-Fine Learning With Image-to-Instance Level Supervision for Fine-Grained Object Detection in Remote Sensing Images (opens in new tab)

Fine-grained object detection (FGOD) models aim to distinguish different subcategories within the same coarse-grained category. Although two-stage object detection frameworks are extensively employed in current FGOD models due to their high detection accuracy, they still face two major problems. First, insufficient discriminability of the backbone features results in frequent misclassification among similar subcategory objects. Second, the limited capability of the backbone features to repres...