Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]

Related tags

Deep LearningDAGL
Overview

Dynamic Attentive Graph Learning for Image Restoration

This repository is for GATIR introduced in the following paper:
Chong Mou, Jian Zhang, Zhuoyuan Wu; Dynamic Attentive Graph Learning for Image Restoration; IEEE International Conference on Computer Vision (ICCV) 2021 [arxiv]

The pre-trained models are available at Google Drive

Requirements

  • Python 3.6
  • PyTorch >= 1.1.0
  • numpy
  • skimage
  • cv2

Introduction

In this paper, we propose an improved graph attention model for image restoration. Unlike previous non-local image restoration methods, our model can assign an adaptive number of neighbors for each query item and construct long-range correlations based on feature patches. Furthermore, our proposed dynamic attentive graph learning can be easily extended to other computer vision tasks. Extensive experiments demonstrate that our proposed model achieves state-of-the-art performance on wide image restoration tasks: synthetic image denoising, real image denoising, image demosaicing, and compression artifact reduction.

Network

Citation

If you find our work helpful in your resarch or work, please cite the following paper.

@inproceedings{mou2021gatir,
  title={Dynamic Attentive Graph Learning for Image Restoration},
  author={Chong, Mou and Jian, Zhang and Zhuoyuan, Wu},
  booktitle={IEEE International Conference on Computer Vision},
  year={2021}
}
Owner
Jian Zhang
Jian Zhang
CNNs for Sentence Classification in PyTorch

Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t

Shawn Ng 956 Dec 19, 2022
Utilities and information for the signals.numer.ai tournament

dsignals Utilities and information for the signals.numer.ai tournament using eodhistoricaldata.com eodhistoricaldata.com provides excellent historical

Degerhan Usluel 23 Dec 18, 2022
[3DV 2020] PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction

PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction International Conference on 3D Vision, 2020 Sai Sagar Jinka1, Rohan

Rohan Chacko 39 Oct 12, 2022
Tutorials and implementations for "Self-normalizing networks"

Self-Normalizing Networks Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print). Vers

Institute of Bioinformatics, Johannes Kepler University Linz 1.6k Jan 07, 2023
House3D: A Rich and Realistic 3D Environment

House3D: A Rich and Realistic 3D Environment Yi Wu, Yuxin Wu, Georgia Gkioxari and Yuandong Tian House3D is a virtual 3D environment which consists of

Meta Research 1.1k Dec 14, 2022
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

300 Nov 22, 2022
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have underg

Nafis Ahmed 1 Dec 28, 2021
Interactive Terraform visualization. State and configuration explorer.

Rover - Terraform Visualizer Rover is a Terraform visualizer. In order to do this, Rover: generates a plan file and parses the configuration in the ro

Tu Nguyen 2.3k Jan 07, 2023
The code is an implementation of Feedback Convolutional Neural Network for Visual Localization and Segmentation.

Feedback Convolutional Neural Network for Visual Localization and Segmentation The code is an implementation of Feedback Convolutional Neural Network

19 Dec 04, 2022
Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"

How Well Do Self-Supervised Models Transfer? This repository hosts the code for the experiments in the CVPR 2021 paper How Well Do Self-Supervised Mod

Linus Ericsson 157 Dec 16, 2022
a simple, efficient, and intuitive text editor

Oxygen beta a simple, efficient, and intuitive text editor Overview oxygen is a simple, efficient, and intuitive text editor designed as more featured

Aarush Gupta 1 Feb 23, 2022
A Fast Knowledge Distillation Framework for Visual Recognition

FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f

Zhiqiang Shen 129 Dec 24, 2022
Subdivision-based Mesh Convolutional Networks

Subdivision-based Mesh Convolutional Networks The official implementation of SubdivNet in our paper, Subdivion-based Mesh Convolutional Networks Requi

Zheng-Ning Liu 181 Dec 28, 2022
Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

A Minimalist Approach to Offline Reinforcement Learning TD3+BC is a simple approach to offline RL where only two changes are made to TD3: (1) a weight

Scott Fujimoto 193 Dec 23, 2022
Effective Use of Transformer Networks for Entity Tracking

Effective Use of Transformer Networks for Entity Tracking (EMNLP19) This is a PyTorch implementation of our EMNLP paper on the effectiveness of pre-tr

5 Nov 06, 2021
Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment

Preference-Planning-Deep-IRL Introduction Check my portfolio post Dependencies Gym stable-baselines3 PyTorch Usage Take Demonstration python3 record.

Tianyu Li 9 Oct 26, 2022
This repository introduces a short project about Transfer Learning for Classification of MRI Images.

Transfer Learning for MRI Images Classification This repository introduces a short project made during my stay at Neuromatch Summer School 2021. This

Oscar Guarnizo 3 Nov 15, 2022
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)

CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa

Bran Zhu 28 Dec 11, 2022
SynNet - synthetic tree generation using neural networks

SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s

Wenhao Gao 60 Dec 29, 2022
Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!

Rubicon Purpose Rubicon is a data science tool that captures and stores model training and execution information, like parameters and outcomes, in a r

Capital One 97 Jan 03, 2023