462 citations · 992 across the 34 of their papers we have counts for
6 papers · 1 filter
Textural-Perceptual Joint Learning for No-Reference Super-Resolution Image Quality Assessment
Yuqing Liu, Qi Jia, Shanshe Wang +2
Image super-resolution (SR) has been widely investigated in recent years. However, it is challenging to fairly estimate the performance of various SR methods, as the lack of reliab…
Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolution
Yuqing Liu, Qi Jia, Xin Fan +3
It is challenging to restore low-resolution (LR) images to super-resolution (SR) images with correct and clear details. Existing deep learning works almost neglect the inherent str…
Rate Distortion Characteristic Modeling for Neural Image Compression
Chuanmin Jia, Ziqing Ge, Shanshe Wang +2
End-to-end optimized neural image compression (NIC) has obtained superior lossy compression performance recently. In this paper, we consider the problem of rate-distortion (R-D) ch…
Visual Analysis Motivated Rate-Distortion Model for Image Coding
Zhimeng Huang, Chuanmin Jia, Shanshe Wang +1
Optimized for pixel fidelity metrics, images compressed by existing image codec are facing systematic challenges when used for visual analysis tasks, especially under low-bitrate c…
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution
Yuqing Liu, Xinfeng Zhang, Shanshe Wang +2
Multi-scale design has been considered in recent image super-resolution (SR) works to explore the hierarchical feature information. Existing multi-scale networks aim to build elabo…
Iterative Network for Image Super-Resolution
Yuqing Liu, Shiqi Wang, Jian Zhang +3
Single image super-resolution (SISR), as a traditional ill-conditioned inverse problem, has been greatly revitalized by the recent development of convolutional neural networks (CNN…