Trustworthy Partial Label Learning with Out-of-distribution Detection

arXiv:2403.06681v1 Announce Type: new
Abstract: Partial Label Learning (PLL) grapples with learning from ambiguously labelled data, and it has been successfully applied in fields such as image recognition. Nevertheless, traditional PLL methods rely on the closed-world assumption, which can be limiting in open-world scenarios and negatively impact model performance and generalization. To tackle these challenges, our study introduces a novel method called PLL-OOD, which is the first to incorporate Out-of-Distribution (OOD) detection into the PLL framework. PLL-OOD significantly enhances model …

abstract arxiv cs.cv data detection distribution fields image image recognition impact open-world performance recognition trustworthy type world