2 citations · 4 across the 8 of their papers we have counts for
3 papers · 1 filter
JPEG AIC2026: A large-scale dataset for fine-grained assessment of image coding
Mohsen Jenadeleh, Jon Sneyers, João Ascenso +8
Recent advances in conventional and learning-based image coding have increased the demand for benchmark datasets that support fine-grained assessment of compressed image quality, p…
Subjective Visual Quality Assessment for High-Fidelity Learning-Based Image Compression
Mohsen Jenadeleh, Jon Sneyers, Panqi Jia +3
Learning-based image compression methods have recently emerged as promising alternatives to traditional codecs, offering improved rate-distortion performance and perceptual quality…
Subjective Image Quality Assessment with Boosted Triplet Comparisons
Hui Men, Hanhe Lin, Mohsen Jenadeleh +1
In subjective full-reference image quality assessment, differences between perceptual image qualities of the reference image and its distorted versions are evaluated, often using d…