The state-of-the-art image restoration model without nonlinear activation functions.
-
Updated
Jul 3, 2024 - Python
The state-of-the-art image restoration model without nonlinear activation functions.
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
Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.
[CVPR 2024] DyBluRF: Dynamic Neural Radiance Fields from Blurry Monocular Video
Convert models from GoldSource engine to Source engine with AI
Unofficial PyTorch implementation of DeepDeblur
Python package for a systems approach to blur estimation and reduction
Demo scripts for the python package pysaber
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
License Plate Recognition using YOLOv8 + EasyOCR + NAFNet
Image Deblurring using Generative Adversarial Networks
Simple but effective implementation of a neural networks able to remove blur from images.
Add a description, image, and links to the deblur topic page so that developers can more easily learn about it.
To associate your repository with the deblur topic, visit your repo's landing page and select "manage topics."