ModelCard.md

Model Cards for IQA-PyTorch

General FR/NR Methods

FR Method Backward AHIQ ✅ PieAPP ✅ LPIPS ✅ DISTS ✅ WaDIQaM ✅ CKDN1 ✅ FSIM ✅ SSIM ✅ MS-SSIM ✅ CW-SSIM ✅ PSNR ✅ VIF ✅ GMSD ✅ NLPD ✅ VSI ✅ MAD ✅

NR Method Backward FID ✖️ CLIPIQA(+) ✅ MANIQA ✅ MUSIQ ✅ DBCNN ✅ PaQ-2-PiQ ✅ HyperIQA ✅ NIMA ✅ WaDIQaM ✅ CNNIQA ✅ NRQM(Ma)2 ✖️ PI(Perceptual Index) ✖️ BRISQUE ✅ ILNIQE ✅ NIQE ✅

[1] This method use distorted image as reference. Please refer to the paper for details.
[2] Currently, only naive random forest regression is implemented and does not support backward.

IQA Methods for Specific Tasks

Task	Method	Description
Underwater IQA	URanker	A ranking-based underwater image quality assessment (UIQA) method, AAAI2023, Arxiv, Github

Outputs of Different Metrics

Note: ~ means that the corresponding numeric bound is typical value and not mathematically guaranteed

model	lower better ?	min	max	DATE	Link
clipiqa	False	0	1	2022	https://arxiv.org/abs/2207.12396
maniqa	False	0		2022	https://arxiv.org/abs/2204.08958
hyperiqa	False	0	1	2020	pdf
cnniqa	False			2014	pdf
tres	False			2022	https://github.com/isalirezag/TReS
musiq	False	~0	~100	2021	https://arxiv.org/abs/2108.05997
musiq-ava	False	~0	~10	2021	https://arxiv.org/abs/2108.05997
musiq-koniq	False	~0	~100	2021	https://arxiv.org/abs/2108.05997
musiq	False			2021	https://arxiv.org/abs/2108.05997
paq2piq	False			2020	pdf
dbcnn	False			2019	https://arxiv.org/bas/1907.02665
brisque	True			2012	pdf
pi	True			2018	https://arxiv.org/abs/1809.07517
nima	False			2018	https://arxiv.org/abs/1709.05424
nrqm	False			2016	https://arxiv.org/abs/1612.05890
ilniqe	True	0		2015	pdf
niqe	True	0		2012	pdf