Gated Fusion Network for Joint Image Deblurring and Super-Resolution
Single-image super-resolution is a fundamental task for vision applications to enhance the image quality with respect to spatial resolution.
Burst ranking for blind multi-image deblurring
The primary motivation is that current bursts deblurring methods do not handle well situations in which misalignment or out-of-context frames are present in the burst.
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency
MediaTek-NeuroPilot/mai21-learned-smartphone-isp
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To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices.
HINet: Half Instance Normalization Network for Image Restoration
Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to boost the performance of image restoration networks.
Intriguing Findings of Frequency Selection for Image Deblurring
Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image.
MC-Blur: A Comprehensive Benchmark for Image Deblurring
Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios.
Improving Image Restoration by Revisiting Global Information Aggregation
Our TLC converts global operations to local ones only during inference so that they aggregate features within local spatial regions rather than the entire large images.
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model
Inspired by the success of DPM, we propose the first DPM based model toward general medical image segmentation tasks, which we named MedSegDiff.
To be or not to be stable, that is the question: understanding neural networks for inverse problems
The solution of linear inverse problems arising, for example, in signal and image processing is a challenging problem since the ill-conditioning amplifies, in the solution, the noise present in the data.
Denoising Diffusion Models for Plug-and-Play Image Restoration
Although diffusion models have shown impressive performance for high-quality image synthesis, their potential to serve as a generative denoiser prior to the plug-and-play IR methods remains to be further explored.