5 citations · 15 across the 7 of their papers we have counts for
7 papers
GAN-based Image Compression with Improved RDO Process
Fanxin Xia, Jian Jin, Lili Meng +2
GAN-based image compression schemes have shown remarkable progress lately due to their high perceptual quality at low bit rates. However, there are two main issues, including 1) th…
JND-Based Perceptual Optimization For Learned Image Compression
Feng Ding, Jian Jin, Lili Meng +1
Recently, learned image compression schemes have achieved remarkable improvements in image fidelity (e.g., PSNR and MS-SSIM) compared to conventional hybrid image coding ones due t…
HVS-Inspired Signal Degradation Network for Just Noticeable Difference Estimation
Jian Jin, Yuan Xue, Xingxing Zhang +3
Significant improvement has been made on just noticeable difference (JND) modelling due to the development of deep neural networks, especially for the recently developed unsupervis…
Full RGB Just Noticeable Difference (JND) Modelling
Jian Jin, Dong Yu, Weisi Lin +3
Just Noticeable Difference (JND) has many applications in multimedia signal processing, especially for visual data processing up to date. It's generally defined as the minimum visu…
Auto-Weighted Layer Representation Based View Synthesis Distortion Estimation for 3-D Video Coding
Jian Jin, Xingxing Zhang, Lili Meng +4
Recently, various view synthesis distortion estimation models have been studied to better serve for 3-D video coding. However, they can hardly model the relationship quantitatively…
A New Image Codec Paradigm for Human and Machine Uses
Sien Chen, Jian Jin, Lili Meng +5
With the AI of Things (AIoT) development, a huge amount of visual data, e.g., images and videos, are produced in our daily work and life. These visual data are not only used for hu…
Local Activity-tuned Image Filtering for Noise Removal and Image Smoothing
Lijun Zhao, Jie Liang, Huihui Bai +3
In this paper, two local activity-tuned filtering frameworks are proposed for noise removal and image smoothing, where the local activity measurement is given by the clipped and no…