Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment
Author:
Affiliation:
1. Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Fujian Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/97/10036333/10145763.pdf?arnumber=10145763
Reference37 articles.
1. Perceivable artifacts in compressed video and their relation to video quality
2. WCDGAN: Weakly Connected Dense Generative Adversarial Network for Artifact Removal of Highly Compressed Images
3. Attribute Artifacts Removal for Geometry-Based Point Cloud Compression
4. A Blind Color Separation Model for Faithful Palette-based Image Recoloring
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1. FLAME-VQA: A Fuzzy Logic-Based Model for High Frame Rate Video Quality Assessment;Future Internet;2023-09-01
2. Blind Video Quality Assessment for Ultra-High-Definition Video Based on Super-Resolution and Deep Reinforcement Learning;Sensors;2023-01-29
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