Graph Fusion Network for Multi-Oriented Object Detection. (arXiv:2205.03562v2 [cs.CV] UPDATED)

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 removal, we propose a novel graph fusion network,
named GFNet, for multi-oriented object detection. Our …

arxiv cv detection fusion graph network