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Found 4 papers, 0 papers with code
Noise-based Enhancement for Foveated Rendering
Novel image synthesis techniques, so-called foveated rendering, exploit this observation and reduce the spatial resolution of synthesized images for the periphery, avoiding the synthesis of high-spatial-frequency details that are costly to generate but not perceived by a viewer.
Analysis and Interpretation of Deep CNN Representations as Perceptual Quality Features
In this paper, to get more insight, we link basic human visual perception to characteristics of learned deep CNN representations as a novel and first attempt to interpret them.
A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution
We identify regions in input images, based on the underlying spatial frequency, which are not generally well reconstructed during Super-Resolution but are most important in terms of visual sensitivity.
Why Are Deep Representations Good Perceptual Quality Features?
In particular, we focus our analysis on fundamental aspects of human perception, such as the contrast sensitivity and orientation selectivity.
