  Compared with MS-COCO, the dataset for the competition has a larger
proportion of large objects which area is greater than 96x96 pixels. As getting
fine boundaries is vitally important for large object segmentation, Mask R-CNN
with PointRend is selected as the base segmentation framework to output
high-quality object boundaries. Besides, a better engine that integrates
ResNeSt, FPN and DCNv2, and a range of effective tricks that including
multi-scale training and test time augmentation are applied to improve
segmentation performance. Our best performance is an ensemble of four models
(three PointRend-based models and SOLOv2), which won the 2nd place in
IJCAI-PRICAI 3D AI Challenge 2020: Instance Segmentation.
