GGT-100K is a 103k-pair LQ-HQ dataset generated via MFMs to enhance real-world generalization of image restoration models.
Realrestorer: Towards generalizable real-world image restoration with large-scale image editing models.arXiv preprint arXiv:2603.25502, 2026
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ControlLight introduces a controllable low-light enhancement model trained on a new large-scale real-world dataset using a misalignment-aware weighted flow matching loss for structural consistency across enhancement levels.
citing papers explorer
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GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration
GGT-100K is a 103k-pair LQ-HQ dataset generated via MFMs to enhance real-world generalization of image restoration models.
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ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement
ControlLight introduces a controllable low-light enhancement model trained on a new large-scale real-world dataset using a misalignment-aware weighted flow matching loss for structural consistency across enhancement levels.