Jul 18, 2024 · This design facilitates single-stage training paradigm to address various degradations while supporting both automatic and user-guided ...

Jul 18, 2024 · This design empowers LMDIR to adopt a single-stage training strategy capable of addressing diverse and complex image restoration tasks, while ...

This design facilitates single-stage training paradigm to address various degradations while supporting both automatic and user-guided restoration. Extensive ...

Jul 18, 2024 · In detail, LMDIR integrates three key prior knowledges: 1) global degradation knowledge from MMLMs, 2) scene-aware contextual descriptions ...

Jul 18, 2024 · This paper proposes a novel approach for all-in-one image restoration that leverages large pre-trained models as priors, without requiring any ...

Jul 19, 2024 · Training-Free Large Model Priors for Multiple-in-One Image Restoration. https://arxiv.org/abs/2407.13181 · 9:42 PM · Jul 19, 2024.

In this paper, we study a challenging problem in image restoration, namely, how to develop an all-in-one method that could recover images from a variety of ...

Training-Free Large Model Priors for Multiple-in-One Image Restoration Xuanhua He, Lang Li, Yingying Wang, Hui Zheng, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie ...

In this paper, we propose lightweight diffusion models for image inpainting that can be trained on a single image, or a few images.

Image restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image.