There are 3 repositories under deblur topic.
The state-of-the-art image restoration model without nonlinear activation functions.
This repository contains a paper collection of the methods for document image processing, including appearance enhancement, deshadowing, dewarping, deblurring, binarization and so on.
The Official Implementation for "HAIR: Hypernetworks-based All-in-One Image Restoration".
Unofficial tensorflow (tf) implementation of DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
[ECCV2022] Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance
Implementation of "Spatio-Temporal Deformable Attention Network for Video Deblurring". (Zhang et al., ECCV 2022)
Amplicon sequence processing workflow using QIIME 2 and Snakemake
:rocket: 这是一个票据自动识别处理的仓库,希望对有类似业务需求的同学有借鉴意义
An Wiener Filter Implementation for Image Processing Task
A PyTorch implementation of the "Deblurring by Realistic Blurring", unofficially
Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.
colab list for image
[CVPR 2024] DyBluRF: Dynamic Neural Radiance Fields from Blurry Monocular Video
Convert models from GoldSource engine to Source engine with AI
A curated list of research papers and datasets related to image and video deblurring.
colab list for video
Unofficial PyTorch implementation of DeepDeblur
Implementation of "Patch-Based Spatio-Temporal Deformable Attention BiRNN for Video Deblurring". (Zhang et al., TCSVT)
Codes for face quality enhancement methods
See https://docs.openvino.ai/2022.3/notebooks/217-vision-deblur-with-output.html#do-inference-on-the-input-image
License Plate Recognition using YOLOv8 + EasyOCR + NAFNet
Pre-Recognition Library.
Restoration of defocused and blurred photos/images
Demo scripts for the python package pysaber
Here we discuss strategies and workflows to analyse metagenomics datasets
Simple but effective implementation of a neural networks able to remove blur from images.
Improving ORB-SLAM3 with deep deblurring networks
Hybrid Image Enhancement platform combining FastAPI and Streamlit for customizable multi-stage pipelines using deep learning. Supports flexible deblurring and dehazing workflows, user authentication, and output history. Easily extendable architecture with pre-trained model weights for advanced image restoration.