Author

Mingxue Tan

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#artificial intelligence Mar 2026

EReCu: Pseudo-label Evolution Fusion and Refinement with Multi-Cue Learning for Unsupervised Camouflage Detection

This work proposes a unified UCOD framework that enhances both the reliability of pseudo-labels and the fidelity of features, and introduces the Multi-Cue Native Perception module, which extracts intrinsic visual priors by integrating low-level texture cues with mid-level semantics.

Shuo Jiang, Gaojian Zhang, Mingxue Tan et al. · arXiv.org · 0 citations