1 citations · 1 across the 2 of their papers we have counts for
7 papers
Image Segmentation via Divisive Normalization: dealing with environmental diversity
Pablo Hernández-Cámara, Jorge Vila-Tomás, Paula Dauden-Oliver +3
Autonomous driving is a challenging scenario for image segmentation due to the presence of uncontrolled environmental conditions and the eventually catastrophic consequences of fai…
On the RAID dataset of perceptual responses: analysis and statistical causes
Paula Daudén-Oliver, David Agost-Beltran, Emilio Sansano-Sansano +4
This work analyzes the RAID dataset to evaluate human responses to affine image distortions, including rotation, translation, scaling, and Gaussian noise. Using Mean Squared Error…
Assessing invariance to affine transformations in image quality metrics
Nuria Alabau-Bosque, Paula Daudén-Oliver, Jorge Vila-Tomás +2
Subjective image quality metrics are usually evaluated according to the correlation with human opinion in databases with distortions that may appear in digital media. However, thes…
Parametric PerceptNet: A bio-inspired deep-net trained for Image Quality Assessment
Jorge Vila-Tomás, Pablo Hernández-Cámara, Valero Laparra +1
Human vision models are at the core of image processing. For instance, classical approaches to the problem of image quality are based on models that include knowledge about human v…
RAID-Database: human Responses to Affine Image Distortions
Paula Daudén-Oliver, David Agost-Beltran, Emilio Sansano-Sansano +3
Image quality databases are used to train models for predicting subjective human perception. However, most existing databases focus on distortions commonly found in digital media a…
Image Statistics Predict the Sensitivity of Perceptual Quality Metrics
Alexander Hepburn, Valero Laparra, Raúl Santos-Rodriguez +1
Previously, Barlow and Attneave hypothesised a link between biological vision and information maximisation. Following Shannon, information was defined using the probability of natu…