1 citations · 1 across the 4 of their papers we have counts for
8 papers · 1 filter
Point Cloud Compression and Objective Quality Assessment: A Survey
Yiling Xu, Yujie Zhang, Shuting Xia +6
The rapid growth of 3D point cloud data, driven by applications in autonomous driving, robotics, and immersive environments, has led to criticals demand for efficient compression a…
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization
Ziyu Shan, Yujie Zhang, Yipeng Liu +1
No-Reference Point Cloud Quality Assessment (NR-PCQA) aims to objectively assess the human perceptual quality of point clouds without relying on pristine-quality point clouds for r…
A Benchmark for Gaussian Splatting Compression and Quality Assessment Study
Qi Yang, Kaifa Yang, Yuke Xing +2
To fill the gap of traditional GS compression method, in this paper, we first propose a simple and effective GS data compression anchor called Graph-based GS Compression (GGSC). GG…
Perception-Guided Quality Metric of 3D Point Clouds Using Hybrid Strategy
Yujie Zhang, Qi Yang, Yiling Xu +1
Full-reference point cloud quality assessment (FR-PCQA) aims to infer the quality of distorted point clouds with available references. Most of the existing FR-PCQA metrics ignore t…
Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment
Ziyu Shan, Yujie Zhang, Qi Yang +5
No-reference point cloud quality assessment (NR-PCQA) aims to automatically evaluate the perceptual quality of distorted point clouds without available reference, which have achiev…
PAME: Self-Supervised Masked Autoencoder for No-Reference Point Cloud Quality Assessment
Ziyu Shan, Yujie Zhang, Qi Yang +3
No-reference point cloud quality assessment (NR-PCQA) aims to automatically predict the perceptual quality of point clouds without reference, which has achieved remarkable performa…