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greatlog/RealDAN

0
View on GitHub↗
38 stars·2 forks·Python·8 viewsarxiv.org/abs/2308.08816↗

RealDAN

Official implementation of our IJCV paper

Features

  • Motion Deblurring - End-to-end alternating optimization for blind super-resolution.

Star history

Star history chart for greatlog/realdanStar history chart for greatlog/realdan

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does greatlog/realdan do?

Official implementation of our IJCV paper

What are the main features of greatlog/realdan?

The main features of greatlog/realdan are: Motion Deblurring.

Which projects share features with greatlog/realdan?

Projects with overlapping indexed features include: hdcvlab/deblurring-by-realistic-blurring — Models, dataset, results. hdcvlab/mc-blur-dataset — We construct a large-scale multi-cause (MC-Blur) dataset for image deblurring. It consists of four blur types: uniform… leiali/reloblur — Paper | Project Page | Video. rimchang/rsblur — Repository for Realistic Blur Synthesis for Learning Image Deblurring. zzh-tech/bit — [CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur. zzh-tech/estrnn — [IJCV][ECCV2020 Spotlight] Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring.

Projects sharing features with RealDAN

These projects share indexed features with RealDAN. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • hdcvlab/deblurring-by-realistic-blurringHDCVLab avatar

    HDCVLab/Deblurring-by-Realistic-Blurring

    66View on GitHub↗

    Models, dataset, results

    Python
    View on GitHub↗66
  • hdcvlab/mc-blur-datasetHDCVLab avatar

    HDCVLab/MC-Blur-Dataset

    46View on GitHub↗

    We construct a large-scale multi-cause (MC-Blur) dataset for image deblurring. It consists of four blur types: uniform blurs, motion blurs by averaging continuous frames, heavy defocus blurs, and real-world blurs. We collect these images from more than 1000 diverse scenes such as buildings, city…

    Python
    View on GitHub↗46
  • leiali/reloblurLeiaLi avatar

    LeiaLi/ReLoBlur

    88View on GitHub↗

    Paper | Project Page | Video

    Python
    View on GitHub↗88
  • rimchang/rsblurrimchang avatar

    rimchang/RSBlur

    117View on GitHub↗

    Repository for Realistic Blur Synthesis for Learning Image Deblurring

    Python
    View on GitHub↗117
Compare all 7 related projects→