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STC: Spatio-Temporal Contrastive Learning for Video Instance Segmentation
[article]
2022
arXiv
pre-print
Video Instance Segmentation (VIS) is a task that simultaneously requires classification, segmentation, and instance association in a video. Recent VIS approaches rely on sophisticated pipelines to achieve this goal, including RoI-related operations or 3D convolutions. In contrast, we present a simple and efficient single-stage VIS framework based on the instance segmentation method CondInst by adding an extra tracking head. To improve instance association accuracy, a novel bi-directional
arXiv:2202.03747v2
fatcat:zltmpnatfrf5hp55dff2csahlm