NBD_KerUnc
Image Deconvolution Model
A repository providing pre-trained models and results for image deconvolution in the presence of kernel/model uncertainty
Project page of the paper 'Deep Learning for Handling Kernel/model Uncertainty in Image Deconvolution' (CVPR 2020)
14 stars
2 watching
5 forks
Language: Python
last commit: over 4 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
| ysnan/vem-nbd | Provides pre-trained models and benchmark results for noise-blind image deblurring, allowing developers to test and compare different approaches. | 14 |
 lingyanruan/lakdnet | An image deblurring model that revisits the use of convolutional neural networks to improve efficiency and performance compared to transformers. | 97 |
 hyeongseokson1/kpac | An implementation of a deep learning model for deblurring images affected by defocus. | 58 |
 preritj/segmentation | Deep learning models for semantic segmentation of images | 100 |
 cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 600 |
 fabianbormann/tensorflow-deconvnet-segmentation | An implementation of a deep learning algorithm for image segmentation using convolutional neural networks | 220 |
 subeeshvasu/2018_subeesh_nbd_cvpr | Provides results and tools for image deblurring using CNNs to handle kernel uncertainty | 5 |
 rwenqi/nbd-glra | A MATLAB implementation of a deep learning-based deconvolution algorithm using generalized low-rank approximation for image restoration. | 21 |
 ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 426 |
 zfturbo/zf_unet_224_pretrained_model | A pre-trained convolutional neural network model for image segmentation tasks. | 214 |
 nicolov/segmentation_keras | An implementation of a deep learning model for image segmentation using Keras and dilated convolutions | 301 |
 swz30/mprnet | A deep learning model designed to progressively restore degraded images by iteratively refining the degradation and its representation in the image | 1,184 |
 zhengpeng7/birefnet | An implementation of a deep learning-based image segmentation model for high-resolution images | 1,319 |
 simonkohl/probabilistic_unet | Reimplementation of a neural network model for conditional segmentation of ambiguous images | 546 |
 yuyang-huang/keras-inception-resnet-v2 | Represents an implementation of the Inception-ResNet v2 deep learning model in Keras. | 180 |