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Grid R-CNN is a well-performed objection detection framework. It transformsthe traditional box offset regression problem into a grid point estimationproblem. With the guidance of the grid points, it can obtain high-qualitylocalization results. However, the speed of Grid R-CNN is not so satisfactory.In this technical report we present Grid R-CNN Plus, a better and fasterversion of Grid R-CNN. We have made several updates that significantly speed upthe framework and simultaneously improve the accuracy. On COCO dataset, theRes50-FPN based Grid R-CNN Plus detector achieves an mAP of 40.4%,outperforming the baseline on the same model by 3.0 points with similarinference time. Code is available at https://github.com/STVIR/Grid-R-CNN .

Grid R-CNN Plus: Faster and Better