76 citations · 100 across the 7 of their papers we have counts for
3 papers · 1 filter
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution
Andreas Lugmayr, Martin Danelljan, Fisher Yu +2
Super-resolution is an ill-posed problem, where a ground-truth high-resolution image represents only one possibility in the space of plausible solutions. Yet, the dominant paradigm…
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
Jingyun Liang, Andreas Lugmayr, Kai Zhang +3
Normalizing flows have recently demonstrated promising results for low-level vision tasks. For image super-resolution (SR), it learns to predict diverse photo-realistic high-resolu…
DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows
Valentin Wolf, Andreas Lugmayr, Martin Danelljan +2
The difficulty of obtaining paired data remains a major bottleneck for learning image restoration and enhancement models for real-world applications. Current strategies aim to synt…