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Graph Fusion Network for Multi-Oriented Object Detection
[article]
2022
arXiv
pre-print
In object detection, non-maximum suppression (NMS) methods are extensively adopted to remove horizontal duplicates of detected dense boxes for generating final object instances. However, due to the degraded quality of dense detection boxes and not explicit exploration of the context information, existing NMS methods via simple intersection-over-union (IoU) metrics tend to underperform on multi-oriented and long-size objects detection. Distinguishing with general NMS methods via duplicate
arXiv:2205.03562v2
fatcat:dg7fbr3dy5cqpbzmgzaispxqoy