8 papers
Towards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric
Bingyang Cui, Yujie Zhang, Qi Yang +2
Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However, existing challenges restrict th…
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…
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…
DPCD: A Quality Assessment Database for Dynamic Point Clouds
Yating Liu, Yujie Zhang, Qi Yang +3
Recently, the advancements in Virtual/Augmented Reality (VR/AR) have driven the demand for Dynamic Point Clouds (DPC). Unlike static point clouds, DPCs are capable of capturing tem…
Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-relevance Degradation Description
Yipeng Liu, Qi Yang, Yujie Zhang +4
The visual quality of point clouds plays a crucial role in the development and broadcasting of immersive media. Therefore, investigating point cloud quality assessment (PCQA) is in…
From Images to Point Clouds: An Efficient Solution for Cross-media Blind Quality Assessment without Annotated Training
Yipeng Liu, Qi Yang, Yujie Zhang +3
We present a novel quality assessment method which can predict the perceptual quality of point clouds from new scenes without available annotations by leveraging the rich prior kno…