1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Overview of Variable Rate Coding in JPEG AI
Panqi Jia, Fabian Brand, Dequan Yu +3
Empirical evidence has demonstrated that learning-based image compression can outperform classical compression frameworks. This has led to the ongoing standardization of learned-ba…
Bit Rate Matching Algorithm Optimization in JPEG-AI Verification Model
Panqi Jia, A. Burakhan Koyuncu, Jue Mao +9
The research on neural network (NN) based image compression has shown superior performance compared to classical compression frameworks. Unlike the hand-engineered transforms in th…
Bit Distribution Study and Implementation of Spatial Quality Map in the JPEG-AI Standardization
Panqi Jia, Jue Mao, Esin Koyuncu +6
Currently, there is a high demand for neural network-based image compression codecs. These codecs employ non-linear transforms to create compact bit representations and facilitate…