English(EN) Weakly Supervised Segmentation as Semantic-Based Regularization

逻辑引导的微调提升弱监督分割模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-13 15:33

研究人员开发了一种新颖的弱监督语义分割方法，将可微分模糊逻辑与深度学习模型相结合。该方法可以将弱标注和领域特定先验知识统一为连续的逻辑约束。这些约束用于微调 SAM 等基础模型，生成改进的伪标签来训练次级分割模型，该模型在基准数据集上已展现出最先进的准确性。 AI

影响引入了一种新的神经符号方法，利用弱监督和模糊逻辑来改进分割模型。

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arXiv cs.AI TIER_1 English(EN) · Jaron Maene · 2026-05-13 15:33

弱监督分割作为语义化正则化

Weakly supervised semantic segmentation (WSSS) trains dense pixel-level segmentation models from partial or coarse annotations such as bounding boxes, scribbles, or image-level tags. While recent work leverages foundation models such as the Segment Anything Model (SAM) to generat…