Ensembled Tricks for Instance Segmentation

Computer Vision has attracted more and more attention with the fast development of deep learning. The instance segmentation area, which extends the Object detection, can better help us comprehend the surrounding environments. In this paper, we ensembled the tricks that can strengthen the model performance for instance segmentation. We do the ablation experiments for the MS-COCO datasets and LVIS datasets. The results demonstrate that the selected tricks can greatly boost the performance. With our tricks, our model achieves the 7th on the LVIS Challenge Track for ICCV 2019 workshop.