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eess.IV2022★ 2 cited
The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement
Danni Huang, Lingyu Zhu, Zihao Lin +3
There is an increasing consensus that the design and optimization of low light image enhancement methods need to be fully driven by perceptual quality. With numerous approaches pro…
eess.IV2021★ 40 cited
No-Reference Image Quality Assessment by Hallucinating Pristine Features
Baoliang Chen, Lingyu Zhu, Chenqi Kong +3
In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination. The proposed quality assessment framework…
eess.IV2020★ 1 cited
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment
Baoliang Chen, Lingyu Zhu, Guo Li +2
In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and -frame rate quality pred…