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A survey on deep neural network pruning: Taxonomy, comparison, analysis, and recommendations
Modern deep neural networks, particularly recent large language models, come with
massive model sizes that require significant computational and storage resources. To …
massive model sizes that require significant computational and storage resources. To …
Image super-resolution: A comprehensive review, recent trends, challenges and applications
Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …
processing to improve the visual perception of the poor-quality images. The key objective of …
Resshift: Efficient diffusion model for image super-resolution by residual shifting
Diffusion-based image super-resolution (SR) methods are mainly limited by the low
inference speed due to the requirements of hundreds or even thousands of sampling steps …
inference speed due to the requirements of hundreds or even thousands of sampling steps …
Mambair: A simple baseline for image restoration with state-space model
Recent years have seen significant advancements in image restoration, largely attributed to
the development of modern deep neural networks, such as CNNs and Transformers …
the development of modern deep neural networks, such as CNNs and Transformers …
Diffir: Efficient diffusion model for image restoration
Diffusion model (DM) has achieved SOTA performance by modeling the image synthesis
process into a sequential application of a denoising network. However, different from image …
process into a sequential application of a denoising network. However, different from image …
Diffbir: Toward blind image restoration with generative diffusion prior
We present DiffBIR, a general restoration pipeline that could handle different blind image
restoration tasks in a unified framework. DiffBIR decouples blind image restoration problem …
restoration tasks in a unified framework. DiffBIR decouples blind image restoration problem …
Diffusion posterior sampling for general noisy inverse problems
Diffusion models have been recently studied as powerful generative inverse problem
solvers, owing to their high quality reconstructions and the ease of combining existing …
solvers, owing to their high quality reconstructions and the ease of combining existing …
Efficient and explicit modelling of image hierarchies for image restoration
The aim of this paper is to propose a mechanism to efficiently and explicitly model image
hierarchies in the global, regional, and local range for image restoration. To achieve that, we …
hierarchies in the global, regional, and local range for image restoration. To achieve that, we …
Denoising diffusion models for plug-and-play image restoration
Abstract Plug-and-play Image Restoration (IR) has been widely recognized as a flexible and
interpretable method for solving various inverse problems by utilizing any off-the-shelf …
interpretable method for solving various inverse problems by utilizing any off-the-shelf …
Promptir: Prompting for all-in-one image restoration
Image restoration involves recovering a high-quality clean image from its degraded version.
Deep learning-based methods have significantly improved image restoration performance …
Deep learning-based methods have significantly improved image restoration performance …