A single point-supervised oriented object detection framework combines scale consistency and symmetry-based angle learning to set new state-of-the-art results on seven aerial benchmarks.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)
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PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection
A single point-supervised oriented object detection framework combines scale consistency and symmetry-based angle learning to set new state-of-the-art results on seven aerial benchmarks.