Image Defocus Deblurring

18 papers with code • 3 benchmarks • 4 datasets

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Most implemented papers

Restormer: Efficient Transformer for High-Resolution Image Restoration

swz30/restormer CVPR 2022

Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.

Uformer: A General U-Shaped Transformer for Image Restoration

ZhendongWang6/Uformer CVPR 2022

Powered by these two designs, Uformer enjoys a high capability for capturing both local and global dependencies for image restoration.

Intriguing Findings of Frequency Selection for Image Deblurring

invokerer/deeprft 23 Nov 2021

Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image.

Improving Image Restoration by Revisiting Global Information Aggregation

megvii-research/TLC 8 Dec 2021

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.

Learning Single Image Defocus Deblurring with Misaligned Training Pairs

liyucs/jdrl 26 Nov 2022

First, in the deblurring module, a bi-directional optical flow-based deformation is introduced to tolerate spatial misalignment between deblurred and ground-truth images.

Defocus Deblurring Using Dual-Pixel Data

Abdullah-Abuolaim/defocus-deblurring-dual-pixel ECCV 2020

DP sensors are used to assist a camera's auto-focus by capturing two sub-aperture views of the scene in a single image shot.

Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data

Abdullah-Abuolaim/recurrent-defocus-deblurring-synth-dual-pixel ICCV 2021

Leveraging these realistic synthetic DP images, we introduce a recurrent convolutional network (RCN) architecture that improves deblurring results and is suitable for use with single-frame and multi-frame data (e. g., video) captured by DP sensors.

Attention! Stay Focus!

tuvovan/ATTSF 16 Apr 2021

We develop a deep convolutional neural networks(CNNs) to deal with the blurry artifacts caused by the defocus of the camera using dual-pixel images.

BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring

junjun-jiang/BaMBNet 31 May 2021

In particular, we estimate the blur amounts of different regions by the internal geometric constraint of the DP data, which measures the defocus disparity between the left and right views.

Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning

Abdullah-Abuolaim/multi-task-defocus-deblurring-dual-pixel-nimat 11 Aug 2021

Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network's ability to learn to deblur the image.