5 citations · 5 across the 16 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…
An Overview of the JPEG AI Learning-Based Image Coding Standard
Semih Esenlik, Yaojun Wu, Zhaobin Zhang +5
JPEG AI is an emerging learning-based image coding standard developed by Joint Photographic Experts Group (JPEG). The scope of the JPEG AI is the creation of a practical learning-b…
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…