论文标题
确定点过程作为NMS的替代方案
Determinantal Point Process as an alternative to NMS
论文作者
论文摘要
我们提出了一个启发的确定点过程（DPP）的非最大抑制（NMS）替代方案，该替代方案已成为所有最先进的对象检测框架中不可或缺的一步。 DPP已被证明可以鼓励子集选择问题的多样性。我们提出NMS作为子集选择问题，并认为直接合并DPP框架可以改善对象检测系统的整体性能。我们提出了一个优化问题，该问题采用与NMS相同的输入，但引入了一种新型的基于亚二型性的子集选择功能。我们的结果强烈表明，本文提出的修改可以为最新的对象检测管道提供一致的改进。
We present a determinantal point process (DPP) inspired alternative to non-maximum suppression (NMS) which has become an integral step in all state-of-the-art object detection frameworks. DPPs have been shown to encourage diversity in subset selection problems. We pose NMS as a subset selection problem and posit that directly incorporating DPP like framework can improve the overall performance of the object detection system. We propose an optimization problem which takes the same inputs as NMS, but introduces a novel sub-modularity based diverse subset selection functional. Our results strongly indicate that the modifications proposed in this paper can provide consistent improvements to state-of-the-art object detection pipelines.
