Weighted Boxes Fusion: ensembling boxes for object detection models
Year: 2019
Type: preprint
Abstract: 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
Source: arXiv (Cornell University)
Authors: Roman Solovyev, Weimin Wang
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2982646900