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RankIQA: Learning from Rankings for No-reference Image Quality Assessment

ICCV 2017 xialeiliu/RankIQA

Furthermore, on the LIVE benchmark we show that our approach is superior to existing NR-IQA techniques and that we even outperform the state-of-the-art in full-reference IQA (FR-IQA) methods without having to resort to high-quality reference images to infer IQA.

NO-REFERENCE IMAGE QUALITY ASSESSMENT

MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessment

CVPR 2020 zhuhancheng/MetaIQA

The underlying idea is to learn the meta-knowledge shared by human when evaluating the quality of images with various distortions, which can then be adapted to unknown distortions easily.

META-LEARNING NO-REFERENCE IMAGE QUALITY ASSESSMENT

Exploiting High-Level Semantics for No-Reference Image Quality Assessment of Realistic Blur Images

18 Oct 2018lidq92/SFA

To guarantee a satisfying Quality of Experience (QoE) for consumers, it is required to measure image quality efficiently and reliably.

BLIND IMAGE QUALITY ASSESSMENT IMAGE QUALITY ESTIMATION NO-REFERENCE IMAGE QUALITY ASSESSMENT

Which Has Better Visual Quality: The Clear Blue Sky or a Blurry Animal?

IEEE Transactions on Multimedia 2018 lidq92/SFA

The proposed method, SFA, is compared with nine representative blur-specific NR-IQA methods, two general-purpose NR-IQA methods, and two extra full-reference IQA methods on Gaussian blur images (with and without Gaussian noise/JPEG compression) and realistic blur images from multiple databases, including LIVE, TID2008, TID2013, MLIVE1, MLIVE2, BID, and CLIVE.

BLIND IMAGE QUALITY ASSESSMENT IMAGE CLASSIFICATION IMAGE QUALITY ESTIMATION NO-REFERENCE IMAGE QUALITY ASSESSMENT

Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment

10 Aug 2020lidq92/LinearityIQA

Experiments on two relevant datasets (KonIQ-10k and CLIVE) show that, compared to MAE or MSE loss, the new loss enables the IQA model to converge about 10 times faster and the final model achieves better performance.

BLIND IMAGE QUALITY ASSESSMENT NO-REFERENCE IMAGE QUALITY ASSESSMENT

No-Reference Quality Assessment of Contrast-Distorted Images using Contrast Enhancement

18 Apr 2019mtobeiyf/CEIQ

No-reference image quality assessment (NR-IQA) aims to measure the image quality without reference image.

NO-REFERENCE IMAGE QUALITY ASSESSMENT SSIM

No-Reference Color Image Quality Assessment: From Entropy to Perceptual Quality

27 Dec 2018jacob6/ENIQA

In the frequency domain, the two-dimensional entropy and the mutual information of the filtered sub-band images are computed as the feature set of the input color image.

NO-REFERENCE IMAGE QUALITY ASSESSMENT

Controllable List-wise Ranking for Universal No-reference Image Quality Assessment

24 Nov 2019GZHU-Image-Lab/CLRIQA

First, to extend the authentically distorted image dataset, we present an imaging-heuristic approach, in which the over-underexposure is formulated as an inverse of Weber-Fechner law, and fusion strategy and probabilistic compression are adopted, to generate the degraded real-world images.

NO-REFERENCE IMAGE QUALITY ASSESSMENT

Quality Aware Generative Adversarial Networks

NeurIPS 2019 lfovia/QAGANS

Generative Adversarial Networks (GANs) have become a very popular tool for implicitly learning high-dimensional probability distributions.

IMAGE GENERATION NO-REFERENCE IMAGE QUALITY ASSESSMENT SSIM