Depicting beyond scores: Advancing image quality assessment through multi-modal language models
We introduce a Depicted image Quality Assessment method (DepictQA), overcoming the
constraints of traditional score-based methods. DepictQA allows for detailed, language …
constraints of traditional score-based methods. DepictQA allows for detailed, language …
Image quality assessment: Measuring perceptual degradation via distribution measures in deep feature spaces
This study aims to develop advanced and training-free full-reference image quality
assessment (FR-IQA) models based on deep neural networks. Specifically, we investigate …
assessment (FR-IQA) models based on deep neural networks. Specifically, we investigate …
Descriptive image quality assessment in the wild
With the rapid advancement of Vision Language Models (VLMs), VLM-based Image Quality
Assessment (IQA) seeks to describe image quality linguistically to align with human …
Assessment (IQA) seeks to describe image quality linguistically to align with human …
DeepWSD: Projecting degradations in perceptual space to wasserstein distance in deep feature space
Existing deep learning-based full-reference IQA (FR-IQA) models usually predict the image
quality in a deterministic way by explicitly comparing the features, gauging how severely …
quality in a deterministic way by explicitly comparing the features, gauging how severely …
Contrastive distortion‐level learning‐based no‐reference image‐quality assessment
A contrastive distortion‐level learning‐based no‐reference image‐quality assessment (NR‐
IQA) framework is proposed in this study to further effectively model various distortion types …
IQA) framework is proposed in this study to further effectively model various distortion types …
Multiscale Sliced Wasserstein Distances as Perceptual Color Difference Measures
Contemporary color difference (CD) measures for photographic images typically operate by
comparing co-located pixels, patches in a “perceptually uniform” color space, or features in a …
comparing co-located pixels, patches in a “perceptually uniform” color space, or features in a …
A full-reference image quality assessment method via deep meta-learning and conformer
S Lang, X Liu, M Zhou, J Luo, H Pu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, a full-reference image quality assessment (FR-IQA) model based on deep
meta-learning and Conformer is proposed. We combine the Conformer architecture with a …
meta-learning and Conformer is proposed. We combine the Conformer architecture with a …
Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation
Opinion-Unaware Blind Image Quality Assessment (OU-BIQA) models aim to predict image
quality without training on reference images and subjective quality scores. Thereinto, image …
quality without training on reference images and subjective quality scores. Thereinto, image …
Hierarchical degradation-aware network for full-reference image quality assessment
X Lan, F Jia, X Zhuang, X Wei, J Luo, M Zhou… - Information …, 2025 - Elsevier
Abstract Full-Reference Image Quality Assessment (FR-IQA) algorithms excel in evaluating
perceptual distortions by comparing reference and distorted images. However, as the …
perceptual distortions by comparing reference and distorted images. However, as the …
Towards a Perceptual Evaluation Framework for Lighting Estimation
J Giroux, MRK Dastjerdi… - Proceedings of the …, 2024 - openaccess.thecvf.com
Progress in lighting estimation is tracked by computing existing image quality assessment
(IQA) metrics on images from standard datasets. While this may appear to be a reasonable …
(IQA) metrics on images from standard datasets. While this may appear to be a reasonable …