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Found 4 papers, 1 papers with code
Image Harmonization with Region-wise Contrastive Learning
Our method attempts to bring together corresponding positive and negative samples by maximizing the mutual information between the foreground and background styles, which desirably makes our harmonization network more robust to discriminate the foreground and background style features when harmonizing composite images.
Mitosis domain generalization in histopathology images -- The MIDOG challenge
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization
To this end, we propose a novel spatial-separated curve rendering network(S$^2$CRNet) for efficient and high-resolution image harmonization for the first time.
Ranked #12 on
Image Harmonization
on iHarmony4
Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge
Mitotic figure count is an important marker of tumor proliferation and has been shown to be associated with patients' prognosis.
