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To solve the first problem, we introduce the new extremely lightweight portrait segmentation model SINet, containing an information blocking decoder and spatial squeeze modules.
SOTA for Portrait Segmentation on EG1800
In our qualitative and quantitative analysis on the EG1800 dataset, we show that our method outperforms various existing lightweight segmentation models.
Compared with other semantic segmentation tasks, portrait segmentation requires both higher precision and faster inference speed.