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- W4384818262 abstract "Due to the scarcity of nighttime semantic segmentation datasets and the high demand for network models, the development of semantic segmentation of nighttime scenes is still very slow. This paper proposes a new network model, ContourNet, which can model multi-level features. In addition, a separate contour network module is designed to accurately predict object contours, improving performance for objects far away, small, or with high contour continuity. A large number of experiments demonstrate that the ContourNet proposed in this paper can significantly improve the semantic segmentation ability of existing models for nighttime images, and can also improve the semantic segmentation accuracy of daytime images to a certain extent, with good generalization abilities. Specifically, after adding the contour module in this article, MIoU has increased by 5.1% on the night dataset Rebecca; MIoU has increased by 2.5% on the daytime dataset CamVid." @default.
- W4384818262 created "2023-07-21" @default.
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- W4384818262 date "2023-07-19" @default.
- W4384818262 modified "2023-09-27" @default.
- W4384818262 title "ContourNet: Research on Contour Based Nighttime Semantic Segmentation" @default.
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- W4384818262 doi "https://doi.org/10.1007/s11063-023-11366-2" @default.
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