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Author

Minchul Kim

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Preprint Sep 2026

Restore What Matters: Lessons from Joint Restoration and Recognition

Recognition pipelines typically adopt a restore-then-recognize workflow, yet decades of experience show that generating visually pleasing images seldom translates to improved recognition. We propose a Joint Restoration-for-Recognition (JR$^2$) paradigm: restore only what downstream tasks truly require, with task signal...

Lan-Qing Guo, Xi-Jun Wang, Minchul Kim et al. · 0 citations

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