274 Repositories
Python un-limited-resolution Libraries
This repository contains data used in the NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems
Proteno This is the data release associated with the corresponding NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deploymen
Run Effective Large Batch Contrastive Learning on Limited Memory GPU
Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr
Official PyTorch implementation of "VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization" (CVPR 2021)
VITON-HD — Official PyTorch Implementation VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization Seunghwan Choi*1, Sunghyun Pa
[ACM MM 2021] Joint Implicit Image Function for Guided Depth Super-Resolution
Joint Implicit Image Function for Guided Depth Super-Resolution This repository contains the code for: Joint Implicit Image Function for Guided Depth
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
Collect super-resolution related papers, data, repositories
Collect super-resolution related papers, data, repositories
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning
Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
Pytorch implementation of Deep Recursive Residual Network for Super Resolution (DRRN)
DRRN-pytorch This is an unofficial implementation of "Deep Recursive Residual Network for Super Resolution (DRRN)", CVPR 2017 in Pytorch. [Paper] You
Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch
SRDenseNet-pytorch Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch (http://openaccess.thecvf.com/content_ICC
Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Real-ESRGAN Colab Demo for Real-ESRGAN . Portable Windows executable file. You can find more information here. Real-ESRGAN aims at developing Practica
Code for Text Prior Guided Scene Text Image Super-Resolution
Code for Text Prior Guided Scene Text Image Super-Resolution
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
vid2vid Project | YouTube(short) | YouTube(full) | arXiv | Paper(full) Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic vid
Project page of the paper 'Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network' (ECCVW 2018)
EPSR (Enhanced Perceptual Super-resolution Network) paper This repo provides the test code, pretrained models, and results on benchmark datasets of ou
PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network"
HAN PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network" This repository is for HAN introduced in the
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
RawVSR This repo contains the official codes for our paper: Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference Xiaoh
PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).
Image Super-Resolution with Non-Local Sparse Attention This repository is for NLSN introduced in the following paper "Image Super-Resolution with Non-
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)
This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the official implementation ESPCN and TecoGAN for more information.
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling @ INTERSPEECH 2021 Accepted
NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc
A PyTorch Reimplementation of TecoGAN: Temporally Coherent GAN for Video Super-Resolution
TecoGAN-PyTorch Introduction This is a PyTorch reimplementation of TecoGAN: Temporally Coherent GAN for Video Super-Resolution (VSR). Please refer to
A linter to manage all your python exceptions and try/except blocks (limited only for those who like dinosaurs).
Manage your exceptions in Python like a PRO Currently in BETA. Inspired by this blog post. I shared the building process of this tool here. “For those
PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021.
GCResNet PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021. The code will
The source codes for ACL 2021 paper 'BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data'
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for
Learning To Have An Ear For Face Super-Resolution
Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on
UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation. Training python train.py --c
Cross-Document Coreference Resolution
Cross-Document Coreference Resolution This repository contains code and models for end-to-end cross-document coreference resolution, as decribed in ou
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation (CVPR 2021, oral presentation) CoCosNet v2: Full-Resolution Correspondence
Evaluation Pipeline for our ECCV2020: Journey Towards Tiny Perceptual Super-Resolution.
Journey Towards Tiny Perceptual Super-Resolution Test code for our ECCV2020 paper: https://arxiv.org/abs/2007.04356 Our x4 upscaling pre-trained model
Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and limited )
GTA-5-Lane-detection Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and
Code for C2-Matching (CVPR2021). Paper: Robust Reference-based Super-Resolution via C2-Matching.
C2-Matching (CVPR2021) This repository contains the implementation of the following paper: Robust Reference-based Super-Resolution via C2-Matching Yum
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging This repository contains an implementation
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J
A list of hyperspectral image super-solution resources collected by Junjun Jiang
A list of hyperspectral image super-resolution resources collected by Junjun Jiang. If you find that important resources are not included, please feel free to contact me.
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"
Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution (CVPR2021)
MASA-SR Official PyTorch implementation of our CVPR2021 paper MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Re
Code and data for ACL2021 paper Cross-Lingual Abstractive Summarization with Limited Parallel Resources.
Multi-Task Framework for Cross-Lingual Abstractive Summarization (MCLAS) The code for ACL2021 paper Cross-Lingual Abstractive Summarization with Limit
Official implement of Paper:A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images
A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images 深度监督影像融合网络DSIFN用于高分辨率双时相遥感影像变化检测 Of
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
Vision Longformer This project provides the source code for the vision longformer paper. Multi-Scale Vision Longformer: A New Vision Transformer for H
This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.
Lite-HRNet: A Lightweight High-Resolution Network Introduction This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution
PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.
End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th
The official pytorch implemention of the CVPR paper "Temporal Modulation Network for Controllable Space-Time Video Super-Resolution".
This is the official PyTorch implementation of TMNet in the CVPR 2021 paper "Temporal Modulation Network for Controllable Space-Time VideoSuper-Resolu
Coreference resolution for English, German and Polish, optimised for limited training data and easily extensible for further languages
Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1
OpenMMLab Image and Video Editing Toolbox
Introduction MMEditing is an open source image and video editing toolbox based on PyTorch. It is a part of the OpenMMLab project. The master branch wo
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution SmallObject Detection
QueryDet-PyTorch This repository is the official implementation of our paper: QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small O
《Dual-Resolution Correspondence Network》(NeurIPS 2020)
Dual-Resolution Correspondence Network Dual-Resolution Correspondence Network, NeurIPS 2020 Dependency All dependencies are included in asset/dualrcne
AOT-GAN for High-Resolution Image Inpainting (codebase for image inpainting)
AOT-GAN for High-Resolution Image Inpainting Arxiv Paper | AOT-GAN: Aggregated Contextual Transformations for High-Resolution Image Inpainting Yanhong
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"
Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r
Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
512x512 flowers after 12 hours of training, 1 gpu 256x256 flowers after 12 hours of training, 1 gpu Pizza 'Lightweight' GAN Implementation of 'lightwe
[CVPR 2021] Unsupervised Degradation Representation Learning for Blind Super-Resolution
DASR Pytorch implementation of "Unsupervised Degradation Representation Learning for Blind Super-Resolution", CVPR 2021 [arXiv] Overview Requirements
Code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction
Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,
git《Investigating Loss Functions for Extreme Super-Resolution》(CVPR 2020) GitHub:
Investigating Loss Functions for Extreme Super-Resolution NTIRE 2020 Perceptual Extreme Super-Resolution Submission. Our method ranked first and secon
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization Official PyTorch implementation for our URST (Ultra-Resolution Sty
An application of high resolution GANs to dewarp images of perturbed documents
Docuwarp This project is focused on dewarping document images through the usage of pix2pixHD, a GAN that is useful for general image to image translat
Repository for "Exploring Sparsity in Image Super-Resolution for Efficient Inference", CVPR 2021
SMSR Reposity for "Exploring Sparsity in Image Super-Resolution for Efficient Inference" [arXiv] Highlights Locate and skip redundant computation in S
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)
Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O
(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan
A command line utility for tracking a stock market portfolio. Primarily featuring high resolution braille graphs.
A command line stock market / portfolio tracker originally insipred by Ericm's Stonks program, featuring unicode for incredibly high detailed graphs even in a terminal.
✨Fast Coreference Resolution in spaCy with Neural Networks
✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv
:id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on
A Fast and Stable GAN for Small and High Resolution Imagesets - pytorch
A Fast and Stable GAN for Small and High Resolution Imagesets - pytorch The official pytorch implementation of the paper "Towards Faster and Stabilize
TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors
TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors This package provides a simulator for vision-based
✨Fast Coreference Resolution in spaCy with Neural Networks
✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv
:id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on
:package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
THE PROJECT IS ARCHIVED Forks: https://github.com/orsinium/forks DepHell -- project management for Python. Why it is better than all other tools: Form
Learning Continuous Image Representation with Local Implicit Image Function
LIIF This repository contains the official implementation for LIIF introduced in the following paper: Learning Continuous Image Representation with Lo
CVPR 2021 Challenge on Super-Resolution Space
Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of
A framework for joint super-resolution and image synthesis, without requiring real training data
SynthSR This repository contains code to train a Convolutional Neural Network (CNN) for Super-resolution (SR), or joint SR and data synthesis. The met
:id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
Deep High-Resolution Representation Learning for Human Pose Estimation (CVPR 2019) News [2020/07/05] A very nice blog from Towards Data Science introd
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Luigi is a Python (3.6, 3.7 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow managemen