RepSNet combines four-direction boundary distance regression with a boundary voting mechanism and reparameterizable encoder-decoder to reach mPQ 0.5633 on the authors' Lizard split and 0.478 on the official CoNIC test set.
IEEE Transactions on Pattern Analysis & Machine Intelligence 13(06), 583–598 (1991)
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RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterization
RepSNet combines four-direction boundary distance regression with a boundary voting mechanism and reparameterizable encoder-decoder to reach mPQ 0.5633 on the authors' Lizard split and 0.478 on the official CoNIC test set.