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Found 10 papers, 2 papers with code
Joint Quality Assessment and Example-Guided Image Processing by Disentangling Picture Appearance from Content
The deep learning revolution has strongly impacted low-level image processing tasks such as style/domain transfer, enhancement/restoration, and visual quality assessments.
Cut-FUNQUE: An Objective Quality Model for Compressed Tone-Mapped High Dynamic Range Videos
High Dynamic Range (HDR) videos have enjoyed a surge in popularity in recent years due to their ability to represent a wider range of contrast and color than Standard Dynamic Range (SDR) videos.
Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos
We demonstrate the usefulness of the new subjective database by benchmarking objective models of visual quality on it.
A FUNQUE Approach to the Quality Assessment of Compressed HDR Videos
Recent years have seen steady growth in the popularity and availability of High Dynamic Range (HDR) content, particularly videos, streamed over the internet.
Joint Deep Image Restoration and Unsupervised Quality Assessment
Deep learning techniques have revolutionized the fields of image restoration and image quality assessment in recent years.
Quality Modeling Under A Relaxed Natural Scene Statistics Model
Information-theoretic image quality assessment (IQA) models such as Visual Information Fidelity (VIF) and Spatio-temporal Reduced Reference Entropic Differences (ST-RRED) have enjoyed great success by seamlessly integrating natural scene statistics (NSS) with information theory.
Edge-Aware Image Color Appearance and Difference Modeling
The perception of color is one of the most important aspects of human vision.
One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment
The Visual Multimethod Assessment Fusion (VMAF) algorithm has recently emerged as a state-of-the-art approach to video quality prediction, that now pervades the streaming and social media industry.
FUNQUE: Fusion of Unified Quality Evaluators
Fusion-based quality assessment has emerged as a powerful method for developing high-performance quality models from quality models that individually achieve lower performances.
A Hitchhiker's Guide to Structural Similarity
The Structural Similarity (SSIM) Index is a very widely used image/video quality model that continues to play an important role in the perceptual evaluation of compression algorithms, encoding recipes and numerous other image/video processing algorithms.
