Image super resolution using with Deep Convolutional Neural Networks
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Updated
Jul 15, 2023 - Jupyter Notebook
Image super resolution using with Deep Convolutional Neural Networks
IKC: Blind Super-Resolution With Iterative Kernel Correction
HiRN: Hierarchical Recurrent Neural Network for Video Super-Resolution (VSR) using Two-Stage Feature Evolution - Official Repository (Applied Soft Computing)
Image Super-Resolution Using ESRGAN
ESRGAN
A PyTorch implementation of ESRGAN. Additionally, a weight file trained for 200 epochs will be provided.
Group-based Bi-Directional Recurrent Wavelet Neural Network for Efficient Video Super-Resolution (VSR) - Official Repository (Pattern Recognition Letters)
This is the repository of the code related to Ruben Moyas's MSc in Data Science Master's Thesis.
The experimental implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" ( SRGAN )
Official implementation of "MAML-SR: Self-Adaptive Super-Resolution Networks via Multi-scale Optimized Attention-aware Meta-Learning" (PRL'23)
Tools to create patches and build CSBDeep deep learning model for md-SR imaging
Demo code for our CVPR'18 paper "FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors" (SPOTLIGHT Presentation)
Accurate Image Super-Resolution Using Very Deep Convolutional Networks (a.k.a VDSR) implementation using TensorFlow
This repository contains an Image Upscaling project using a Generative Adversarial Network (GAN) model.
Super Resolution
A flow to compile ESPCN (super resolution) using TVM and run the compiled model on CPU to calculate PSNR
Wei Li person blog note
PyTorch implements "Deep Back-Projection Networks for Single Image Super-resolution” paper.
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