{"ID":2857009,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.10055","arxiv_id":"2510.10055","title":"Incomplete Multi-Label Image Recognition by Co-learning Semantic-Aware Features and Label Recovery","abstract":"Multi-label image recognition with incomplete labels is a challenging yet vital task in computer vision, which faces two fundamental challenges: learning semantic-aware features and recovering missing labels. In this paper, we propose a Co-learning framework for Semantic-aware features and Label recovery (CSL), designed to address both challenges in a unified learning paradigm. Specifically, we develop a semantic-related feature learning module that captures robust semantic-related representations by discovering semantic information and label correlations. Furthermore, a semantic-guided feature enhancement module is introduced to generate highly discriminative semantic-aware features by effectively aligning visual and semantic spaces. Finally, we present a collaborative learning framework that integrates semantic-aware feature learning with label recovery. This framework not only dynamically enhances the discriminability of semantic-aware features but also adaptively infers and recovers missing labels, thereby forming a mutually reinforcing mechanism between the two processes. Extensive experiments on three widely used public datasets (MS-COCO, VOC2007, and NUS-WIDE) demonstrate that CSL outperforms state-of-the-art methods for incomplete multi-label image recognition.","short_abstract":"Multi-label image recognition with incomplete labels is a challenging yet vital task in computer vision, which faces two fundamental challenges: learning semantic-aware features and recovering missing labels. In this paper, we propose a Co-learning framework for Semantic-aware features and Label recovery (CSL), designe...","url_abs":"https://arxiv.org/abs/2510.10055","url_pdf":"https://arxiv.org/pdf/2510.10055v2","authors":"[\"Zhi-Fen He\",\"Ren-Dong Xie\",\"Bo Li\",\"Bin Liu\",\"Jin-Yan Hu\"]","published":"2025-10-11T06:43:43Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}