In this report, we present our object detection/instance segmentation system, MegDetV2, which works in a two-pass fashion, first to detect instances then to obtain segmentation. Our baseline detector is mainly built on a new designed RPN, called RPN++. On the COCO-2019 detection/instance-segmentation test-dev dataset, our system achieves 61.0/53.1 mAP, which surpassed our 2018 winning results by 5.0/4.2 respectively. We achieve the best results in COCO Challenge 2019 and 2020.
翻译:在本报告中,我们介绍了我们的物体探测/内分分离系统MegDetV2,该系统以双向方式工作,先是检测,然后是检测,然后获得分解。我们的基线检测器主要建在一个新的设计RPN(RPN+++)上。在COCO-2019检测/内分层测试-dev数据集上,我们的系统实现了61.0/53.1 mAP,分别比2018年的得分结果高出5.0/4.2。我们在COCO挑战2019和2020年中取得了最佳成果。