AI RESEARCH
Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images
arXiv CS.CV
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ArXi:2605.10162v1 Announce Type: new Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention for effectively reducing annotation redundancy in densely remote sensing scenes. However, (1) the sparse data reliance on class-dependent sampling, and (2) the lack of in-depth investigation into the characteristics of sparse samples hinders its further development. This paper proposes an active learning-based sparsely annotated oriented object detection (SAOOD) method, termed Active