Text-guided Explorable Image Super-resolution

arXiv:2403.01124v1 Announce Type: new
Abstract: In this paper, we introduce the problem of zero-shot text-guided exploration of the solutions to open-domain image super-resolution. Our goal is to allow users to explore diverse, semantically accurate reconstructions that preserve data consistency with the low-resolution inputs for different large downsampling factors without explicitly training for these specific degradations. We propose two approaches for zero-shot text-guided super-resolution - i) modifying the generative process of text-to-image \textit{T2I} diffusion models to promote consistency with low-resolution inputs, …

abstract arxiv cs.cv data diverse domain downsampling exploration explore image inputs low paper solutions text training type zero-shot