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Weak support annotations can significantly degrade segmentation performance, but SADe cleans these inputs to boost accuracy by over 19 mIoU points in challenging scenarios.
Vision Mamba's accuracy can be significantly improved just by swapping out the default discretization method, with bilinear discretization offering the best balance of performance and efficiency.