AI RESEARCH
Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
arXiv CS.CV
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ArXi:2605.28239v1 Announce Type: new Semi-supervised referring expression segmentation (SS-RES) aims to achieve precise pixel-level language grounding under limited annotation, yet suffers from limited supervision and unreliable pseudo-labels when exploiting unlabeled image-text pairs. In this work, we propose Learning to Label, a reinforced self-evolving framework (L2L) that casts pseudo-label construction as a learnable decision-making process.