Joint COCO and Mapillary Workshop at ICCV 2019: COCO Instance Segmentation Challenge Track

• URL: http://arxiv.org/abs/2010.02475v1
• Date: Tue, 6 Oct 2020 04:49:37 GMT
• Title: Joint COCO and Mapillary Workshop at ICCV 2019: COCO Instance Segmentation Challenge Track
• Authors: Zeming Li, Yuchen Ma, Yukang Chen, Xiangyu Zhang, Jian Sun
• Abstract summary: MegDetV2 works in a two-pass fashion, first to detect instances then to obtain segmentation. 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.
• Score: 87.90450014797287
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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