In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation. Previously, most instance segmentation methods heavily rely on object detection and perform mask prediction based on bounding boxes or dense centers. 2022: Tianheng Cheng, Xinggang Wang, Shaoyu Chen, Wenqiang Zhang, Q. Zhang, Chang Huang, Zhaoxiang Zhang, Wenyu Liu Ranked #1 on Real-time Instance Segmentation on MSCOCO https://arxiv.org/pdf/2203.12827v1.pdf
Version: 20240320
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