GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration 事件

GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration arXiv:2605.31039v1 Announce Type: new Abstract: Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail to model real-world degradations, while real-world paired datasets are expensive and difficult to capture. As a result, IR models trained on these datasets show limited generalization in real-world scenarios. In this wo