Guillaume Berger

MagnifiQ: Patch-aware Text Guided Progressive Upscaling for High-Resolution Image Restoration

MagnifiQ is introduced, an image restoration framework that progressively upscales and restores images across resolutions, e.g., from 1024x1024 to 4096x4096, and leverages a pre-trained text-to-image diffusion model such as SDXL and adapts it for more scalable high-resolution inference by replacing its original self-attention layers with convolutional operations whose computational cost grows linearly with image resolution.