Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detection. (arXiv:2206.13728v1 [cs.CV])

Complicated underwater environments bring new challenges to object detection,
such as unbalanced light conditions, low contrast, occlusion, and mimicry of
aquatic organisms. Under these circumstances, the objects captured by the
underwater camera will become vague, and the generic detectors often fail on
these vague objects. This work aims to solve the problem from two perspectives:
uncertainty modeling and hard example mining. We propose a two-stage underwater
detector named boosting R-CNN, which comprises three key components. First, a
new region proposal …

arxiv boosting cnn cv detection error r-cnn