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Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild
Weixia Zhang, Kede Ma, Guangtao Zhai +1
Performance of blind image quality assessment (BIQA) models has been significantly boosted by end-to-end optimization of feature engineering and quality regression. Nevertheless, d…
Perceptual Quality Assessment of Omnidirectional Images as Moving Camera Videos
Xiangjie Sui, Kede Ma, Yiru Yao +1
Omnidirectional images (also referred to as static 360° panoramas) impose viewing conditions much different from those of regular 2D images. How do humans perceive image distortion…
Comparison of Image Quality Models for Optimization of Image Processing Systems
Keyan Ding, Kede Ma, Shiqi Wang +1
The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments. Perceptual datasets gathe…
Image Quality Assessment: Unifying Structure and Texture Similarity
Keyan Ding, Kede Ma, Shiqi Wang +1
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original. Relative to human observers, these measures are overly sen…
Active Fine-Tuning from gMAD Examples Improves Blind Image Quality Assessment
Zhihua Wang, Kede Ma
The research in image quality assessment (IQA) has a long history, and significant progress has been made by leveraging recent advances in deep neural networks (DNNs). Despite high…
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
Haotao Wang, Tianlong Chen, Zhangyang Wang +1
The learning of hierarchical representations for image classification has experienced an impressive series of successes due in part to the availability of large-scale labeled data…