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Weighted Boxes Fusion: ensembling boxes for object detection models
lib:78248f99815f5626 (v1.0.0)
Authors: Roman Solovyev,Weimin Wang,Tatiana Gabruseva
ArXiv: 1910.13302
Document: PDF DOI
Artifact development version: GitHub
Abstract URL: https://arxiv.org/abs/1910.13302v2
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 https://github.com/ZFTurbo/Weighted-Boxes-Fusion
ArXiv: 1910.13302
Document: PDF DOI
Artifact development version: GitHub
Abstract URL: https://arxiv.org/abs/1910.13302v2
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 https://github.com/ZFTurbo/Weighted-Boxes-Fusion
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