3 accepted papers
Real-world super-resolution (SR) is challenging due to complex degradations. HYPIR, a recent state-of-the-art diffusion-based restoration model, struggles to deal with this task in a single step. Although a naive two-step cascade improves the results, over-saturation, limited fine-grained details, a…
We introduce UniCon, a novel architecture designed to enhance control and efficiency in training adapters for large-scale diffusion models. Unlike existing methods that rely on bidirectional interaction between the diffusion model and control adapter, UniCon implements a unidirectional flow from the…
We introduce SUPIR (Scaling-UP Image Restoration) a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up. Leveraging multi-modal techniques and advanced generative prior SUPIR marks a significant advance in intelligent and realistic image restorat…