12 citations · 45 across the 35 of their papers we have counts for
9 papers · 1 filter
Benchmarking and Learning Multi-Dimensional Quality Evaluator for Text-to-3D Generation
Yujie Zhang, Bingyang Cui, Qi Yang +2
Text-to-3D generation has achieved remarkable progress in recent years, yet evaluating these methods remains challenging for two reasons: i) Existing benchmarks lack fine-grained e…
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…
Inter-Frame Coding for Dynamic Meshes via Coarse-to-Fine Anchor Mesh Generation
He Huang, Lizhi Hou, Qi Yang +1
In the current Video-based Dynamic Mesh Coding (V-DMC) standard, inter-frame coding is restricted to mesh frames with constant topology. Consequently, temporal redundancy is not fu…
A Hierarchical Compression Technique for 3D Gaussian Splatting Compression
He Huang, Wenjie Huang, Qi Yang +2
3D Gaussian Splatting (GS) demonstrates excellent rendering quality and generation speed in novel view synthesis. However, substantial data size poses challenges for storage and tr…
Asynchronous Feedback Network for Perceptual Point Cloud Quality Assessment
Yujie Zhang, Qi Yang, Ziyu Shan +1
Recent years have witnessed the success of the deep learning-based technique in research of no-reference point cloud quality assessment (NR-PCQA). For a more accurate quality predi…
Explicit-NeRF-QA: A Quality Assessment Database for Explicit NeRF Model Compression
Yuke Xing, Qi Yang, Kaifa Yang +2
In recent years, Neural Radiance Fields (NeRF) have demonstrated significant advantages in representing and synthesizing 3D scenes. Explicit NeRF models facilitate the practical Ne…
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…