Remember and Reuse: Cross-Task Blind Image Quality Assessment via Relevance-aware Incremental Learning

This repository contains PyTorch code of our paper: Remember and Reuse: Cross-Task Blind Image Quality Assessment via Relevance-aware Incremental Learning (ACM Multimedia 2021).

Introduction

1. Cross-task blind image quality assessment process.

2. The flow diagram of Remember and Reuse network(R&R-Net) leaning a sequence of BIQA tasks.

3. Change in SRCC of the first task in the incremental learning process.

Requirements

Ubuntu 18.04
python == 3.6
torch == 1.2.0
torchvision == 0.4.0
tensorboard == 2.6.0
future == 0.18.2
scipy == 1.5.4

Usage

1. Datasets and pre-trained Model

Download crop_IQA_Datasets, unzip it and put it in ./data; Download ImageNet pre-trained model, put it in ./imagenet.

2. Training and testing

python main.py