GGT-100K is a 103k-pair LQ-HQ dataset generated via MFMs to enhance real-world generalization of image restoration models.
A preliminary ex- ploration towards general image restoration
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An RL-trained lightweight agent uses MLLM perceptual rewards to perform efficient label-free image restoration, matching SOTA on full-reference metrics and surpassing prior work on no-reference metrics.
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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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Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedback
An RL-trained lightweight agent uses MLLM perceptual rewards to perform efficient label-free image restoration, matching SOTA on full-reference metrics and surpassing prior work on no-reference metrics.