Title
Ensembled Tricks for Instance Segmentation.
Abstract
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.
Year
DOI
Venue
2020
10.1109/IWCMC48107.2020.9148439
IWCMC
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Runze Zhang142.83
Liang Jin200.34
Yongfang Chen300.34
Zhenhua Guo465.88
Kun Zhao500.34
Yaqian Zhao636.47