Python Correference-resolution Resources

BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

DASR Paper Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution Jie Liang, Hui Zeng, and Lei Zhang. In arxiv preprint. Abs

A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution (CVPR2022) https://arxiv.org/abs/2203.09388 Jianqi Ma, Zheto

Crosslingual Coreference Coreference is amazing but the data required for training a model is very scarce. In our case, the available training for non

HAT [Paper Link] Activating More Pixels in Image Super-Resolution Transformer Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong BibTeX @article{ch

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

Coreferee Author: Richard Paul Hudson, Explosion AI 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 French 1.2.3 German 1.2

Reference-based Video Super-Resolution (RefVSR) Official PyTorch Implementation of the CVPR 2022 Paper Project | arXiv | RealMCVSR Dataset This repo c

ELAN Codes for "Efficient Long-Range Attention Network for Image Super-resolution", arxiv link. Dependencies & Installation Please refer to the follow

Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e

StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

PGNet Pyramid Grafting Network for One-Stage High Resolution Saliency Detection. CVPR 2022, CVPR 2022 (arXiv 2204.05041) Abstract Recent salient objec

ARM-Net Dependencies Python 3.6 Pytorch 1.7 Results Train Data preprocessing cd data_scripts python extract_subimages_test.py python data_augmentation

FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T

HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation by Lukas Hoyer, Dengxin Dai, and Luc Van Gool [Arxiv] [Paper] Overview Unsup

V0-DBM This is a high-resolution differential pulley system belt mod for the Z-axis on Voron 0 with optional Kirigami Bed support. NOTE: Alpha version

Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima

MRS-SLAM for long-term place recognition In this work, we imply an multi-resolution sambling based visual place recognition method. This work is based

S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install

Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a

Real Cascade U-Nets for Anime Image Super Resolution 中文 | English 🔥 Real-CUGAN

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta

VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer

Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base

Revisiting RCAN: Improved Training for Image Super-Resolution Introduction Image super-resolution (SR) is a fast-moving field with novel architectures

Pyramid Transformer Net (PTNet) Project | Paper Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis. PTNet: A Hi

T2Net Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021) [Paper][Code] Dependencies numpy==1.18.5 scikit_image==

Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN Introduction Image super-resolution (SR) is the process of recovering high-resoluti

Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a

Earth - Topography grid at 10 arc-minute resolution Global 10 arc-minute resolution grids of topography (ETOPO1 ice-surface) referenced to mean sea-le

DPT Official Pytorch implementation of the paper "Detail-Preserving Transformer for Light Field Image Super-Resolution" accepted by AAAI 2022 . Update

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

UAV Solar-Sensor Angle Calculation Table of Contents About The Project Built With Getting Started Prerequisites Installation Datasets Contributing Lic

GLNet for Memory-Efficient Segmentation of Ultra-High Resolution Images Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-

subpixel: A subpixel convolutional neural network implementation with Tensorflow Left: input images / Right: output images with 4x super-resolution af

PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

[SIGGRAPH Asia 2021] Time-Travel Rephotography [Project Website] Many historical people were only ever captured by old, faded, black and white photos,

SRAugmentation Augmentation for Single-Image-Super-Resolution Implimentation CutBlur Cutout CutMix Cutup CutMixup Blend RGBPermutation Identity OneOf

HKDnet Paper Title: "Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution" Email: 18186470991@163.

Single Image Super-Resolution with EDSR, WDSR and SRGAN A Tensorflow 2.x based implementation of Enhanced Deep Residual Networks for Single Image Supe

Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

edge-SR: Super Resolution For The Masses Citation Pablo Navarrete Michelini, Yunhua Lu and Xingqun Jiang. "edge-SR: Super-Resolution For The Masses",

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

Fusformer Code for the paper: "Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution" Plateform Python 3.8.5 + Pytor

Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.

HiT-GAN Official TensorFlow Implementation HiT-GAN presents a Transformer-based generator that is trained based on Generative Adversarial Networks (GA

openslide_patcher Makes patches from huge resolution .svs slide files using openslide Example collage I made from outputs:

Latent Diffusion Models arXiv | BibTeX High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach*, Andreas Blattmann*, Dominik Lorenz

Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase

StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang

A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind

Latent Diffusion Models Requirements A suitable conda environment named ldm can be created and activated with: conda env create -f environment.yaml co

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization (CVPR 2020) News: [2020/06/15] Demo with Google Colab (i

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since

DRSAN A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution Karam Park, Jae Woong Soh, and Nam Ik Cho Environments U

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:

Uniplot Lightweight plotting to the terminal. 4x resolution via Unicode. When working with production data science code it can be handy to have plotti

Fast and Context-Aware Framework for Space-Time Video Super-Resolution Preparation Dependencies PyTorch 1.2.0 CUDA 10.0 DCNv2 cd model/DCNv2 bash make

UNITER-Based Situated Coreference Resolution with Rich Multimodal Input: arXiv MMCoref_cleaned Code for the MMCoref task of the SIMMC 2.0 dataset. Pre

BasicLFSR BasicLFSR is an open-source and easy-to-use Light Field (LF) image Super-Ressolution (SR) toolbox based on PyTorch, including a collection o

Shorts-Tik-Tok-Creator Takes a video as an input and creates a video which is suitable to upload on Youtube Shorts and Tik Tok (1080x1920 resolution).

ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)

High-resolution networks (HRNets) for Image classification News [2021/01/20] Add some stronger ImageNet pretrained models, e.g., the HRNet_W48_C_ssld_

pmapper pmapper is a super-resolution and deconvolution toolkit for python 3.6+. PMAP stands for Poisson Maximum A-Posteriori, a highly flexible and a

RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain

AdaDM AdaDM: Enabling Normalization for Image Super-Resolution. You can apply BN, LN or GN in SR networks with our AdaDM. Pretrained models (EDSR*/RDN

NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

SinGAN Project | Arxiv | CVF | Supplementary materials | Talk (ICCV`19) Official pytorch implementation of the paper: "SinGAN: Learning a Generative M

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

Deep High-Resolution Representation Learning for Human Pose Estimation (accepted to CVPR2019) News If you are interested in internship or research pos

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization News: [2020/05/04] Added EGL rendering option for training data g

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized C

RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

The first open source high resolution dataset for face swapping!!! A high resolution version of VGGFace2 for academic face editing purpose

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,

cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut

GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral) [Project] [Paper] [Demo] [Related Work: A2RL (for Auto Image Cropping)] [C

Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]

srez Image super-resolution through deep learning. This project uses deep learning to upscale 16x16 images by a 4x factor. The resulting 64x64 images

Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl

Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for

High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v

Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a

Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for

ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

Sparse deconvolution Python v0.3.0 Official Python implementation of the 'Sparse deconvolution', and the CPU (NumPy) and GPU (CuPy) calculation backen

TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr