17 citations · 23 across the 5 of their papers we have counts for
6 papers
R4-CGQA: Retrieval-based Vision Language Models for Computer Graphics Image Quality Assessment
Zhuangzi Li, Jian Jin, Shilv Cai +1
Immersive Computer Graphics (CGs) rendering has become ubiquitous in modern daily life. However, comprehensively evaluating CG quality remains challenging for two reasons: First, e…
MUGSQA: Novel Multi-Uncertainty-Based Gaussian Splatting Quality Assessment Method, Dataset, and Benchmarks
Tianang Chen, Jian Jin, Shilv Cai +2
Gaussian Splatting (GS) has recently emerged as a promising technique for 3D object reconstruction, delivering high-quality rendering results with significantly improved reconstruc…
Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization Problem
Qiwen Zhu, Yanjie Wang, Shilv Cai +5
Training Single-Image Super-Resolution (SISR) models using pixel-based regression losses can achieve high distortion metrics scores (e.g., PSNR and SSIM), but often results in blur…
Powerful Lossy Compression for Noisy Images
Shilv Cai, Xiaoguo Liang, Shuning Cao +4
Image compression and denoising represent fundamental challenges in image processing with many real-world applications. To address practical demands, current solutions can be categ…
Make Lossy Compression Meaningful for Low-Light Images
Shilv Cai, Liqun Chen, Sheng Zhong +3
Low-light images frequently occur due to unavoidable environmental influences or technical limitations, such as insufficient lighting or limited exposure time. To achieve better vi…
High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation
Shilv Cai, Zhijun Zhang, Liqun Chen +3
Learning-based methods have effectively promoted the community of image compression. Meanwhile, variational autoencoder (VAE) based variable-rate approaches have recently gained mu…