跳跃式监视
计算机科学
编码(集合论)
目标检测
对象(语法)
背景(考古学)
最小边界框
人工智能
融合
数据挖掘
模式识别(心理学)
计算机视觉
图像(数学)
集合(抽象数据类型)
程序设计语言
地理
语言学
哲学
考古
作者
Roman Solovyev,Weimin Wang
摘要
In this work, we present a novel method for combining predictions of object detection models: weighted boxes fusion. Our algorithm utilizes confidence scores of all proposed bounding boxes to constructs the averaged boxes. We tested method on several datasets and evaluated it in the context of the Open Images and COCO Object Detection tracks, achieving top results in these challenges. The source code is publicly available at this https URL
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