Preprint
Aug 2026
Continuity-Driven Representation Learning for Industrial Defect Detection
A continuity-driven representation regularization framework that exploits normal-dominant regions as dense auxiliary supervision for industrial defect detection, particularly when annotated data are scarce is proposed.
Minjong Kim, Hyun Jun Kim, Jeongrae Kim et al.
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