42 datasets found

PKU-I2IQA: An image-to-image quality assessment database for AI-generated images

AIGCIQA2023: A large-scale image quality assessment database for AI-generated images: from the perspectives of quality, authenticity and correspondence

AGIQA-3K: An open database for AI-generated image quality assessment

The dataset used for training and testing the proposed model.

This paper uses robust statistics and curvelet transform to learn a general-purpose no-reference (NR) image quality assessment (IQA) model.

Face sketch synthesis has wide applications ranging from digital entertainments to law enforcements. Objective image quality assessment scores and face recognition accuracy are...

The Waterloo Exploration Database is a large-scale dataset for testing the generalization performance of image quality assessment models.

The dataset used for training the spatial module on multiple blind image quality assessment (BIQA) datasets.

The dataset used for training the spatial module on multiple blind image quality assessment (BIQA) datasets.

The IQA dataset is a benchmark for image quality assessment, which contains a large collection of images with varying quality.

The OCTA-25K-IQA-SEG dataset for image quality assessment

Four publicly available HDR-IQA datasets are adopted for benchmarking: Narwaria2013, Valenzise2014, Zerman2017, and UPIQ.

Four publicly available HDR-IQA datasets are adopted for benchmarking: Narwaria2013, Valenzise2014, Zerman2017, and UPIQ.

Four publicly available HDR-IQA datasets are adopted for benchmarking: Narwaria2013, Valenzise2014, Zerman2017, and UPIQ.

Four publicly available HDR-IQA datasets are adopted for benchmarking: Narwaria2013, Valenzise2014, Zerman2017, and UPIQ.

A perceptual quality assessment database for AI-generated images (AGIs) named AGIQA-1K, which consists of 1,080 AGIs generated from diffusion models.

The TID2013 database contains 3000 distorted images generated by applying 24 distortion operations at 5 levels to 25 pristine images.

The dataset used for blind image quality assessment

The CSIQ database contains 866 distorted images generated by applying 5 distortion operations at 3 ∼ 5 levels to 30 pristine images.

The dataset used for blind image quality assessment