Search Results for author:
Found 3 papers, 2 papers with code
Adapting Pretrained Networks for Image Quality Assessment on High Dynamic Range Displays
Conventional image quality metrics (IQMs), such as PSNR and SSIM, are designed for perceptually uniform gamma-encoded pixel values and cannot be directly applied to perceptually non-uniform linear high-dynamic-range (HDR) colors.
Learning Neural Implicit Representations with Surface Signal Parameterizations
Traditional explicit object representations commonly couple the 3D shape data with auxiliary surface-mapped image data, such as diffuse color textures and fine-scale geometric details in normal maps that typically require a mapping of the 3D surface onto a plane, i. e., a surface parameterization; implicit representations, on the other hand, cannot be easily textured due to lack of configurable surface parameterization.
VTAMIQ: Transformers for Attention Modulated Image Quality Assessment
Following the major successes of self-attention and Transformers for image analysis, we investigate the use of such attention mechanisms in the context of Image Quality Assessment (IQA) and propose a novel full-reference IQA method, Vision Transformer for Attention Modulated Image Quality (VTAMIQ).
