Blind quality assessment for image superresolution using deep two-stream convolutional networks, published in Information Sciences 2020

Matlab code for calculate the SROCC and PLCC metrics (code for image quality assessment).

Include MuCAN, LAPAR, etc.

[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Conformer and Blind Noisy Students for Improved Image Quality Assessment

[CVPRW 2021] Codes for Region-Adaptive Deformable Network for Image Quality Assessment

[CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

This repository is an implementation of the paper "Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Search".

Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices, ACM Multimedia 2021

PyTorch code for NeurIPS2021 paper "Uncertainty-Driven Loss for Single Image Super-Resolution"

[CVPRW & CLIC 2022 - Perceptual Metrics] Image Quality Assessment with Transformers and Multi-Metric Fusion Modules

Pytorch code for our AAAI2022 Oral paper "Content-Variant Reference Image Quality Assessment via Knowledge Distillation"

IQA: Deep Image Structure and Texture Similarity Metric

(ECCV2020 Workshops) Efficient Image Super-Resolution Using Pixel Attention.

models and code for "Efficient Image Super Resolution using Vast Receptive Field Attention"

A Flexible and Unified Image Restoration Framework (PyTorch), including state-of-the-art image restoration model. Such as NAFNet, Restormer, MPRNet, MIMO-UNet, SCUNet, SwinIR, HINet, etc. ⭐⭐⭐⭐⭐⭐

Pytorch implementation of cnn network

[CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

[ECCV2022] Efficient Long-Range Attention Network for Image Super-resolution

DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-Resolution (TMM 2023)

[official] No reference image quality assessment based Semantic Feature Aggregation, published in ACM MM 2017, TMM 2019

Hierarchical Pixel Integration for Lightweight Image Super-Resolution

[ICCV'21] CKDN: Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

Handy image viewer based on PyQt5. Convenient for viewing and comparing :-)

[CVPR 2021] Unsupervised Degradation Representation Learning for Blind Super-Resolution

Collect super-resolution related papers, data, repositories