| Autor: |
Zhang, Zicheng, Sun, Wei, Wu, Haoning, Zhou, Yingjie, Li, Chunyi, Chen, Zijian, Min, Xiongkuo, Zhai, Guangtao, Lin, Weisi |
| Předmět: |
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| Zdroj: |
ACM Transactions on Multimedia Computing, Communications & Applications; Jun2024, Vol. 20 Issue 6, p1-19, 19p |
| Abstrakt: |
Nowadays, most three-dimensional model quality assessment (3DQA) methods have been aimed at improving accuracy. However, little attention has been paid to the computational cost and inference time required for practical applications. Model-based 3DQA methods extract features directly from the 3D models, which are characterized by their high degree of complexity. As a result, many researchers are inclined towards utilizing projection-based 3DQA methods. Nevertheless, previous projection-based 3DQA methods directly extract features from multi-projections to ensure quality prediction accuracy, which calls for more resource consumption and inevitably leads to inefficiency. Thus, in this article, we address this challenge by proposing a no-reference (NR) projection-based Grid Mini-patch Sampling 3D Model Quality Assessment (GMS-3DQA) method. The projection images are rendered from six perpendicular viewpoints of the 3D model to cover sufficient quality information. To reduce redundancy and inference resources, we propose a multi-projection grid mini-patch sampling strategy (MP-GMS), which samples grid mini-patches from the multi-projections and forms the sampled grid mini-patches into one quality mini-patch map (QMM). The Swin-Transformer tiny backbone is then used to extract quality-aware features from the QMMs. The experimental results show that the proposed GMS-3DQA outperforms existing state-of-the-art NR-3DQA methods on the point cloud quality assessment databases for both accuracy and efficiency. The efficiency analysis reveals that the proposed GMS-3DQA requires far less computational resources and inference time than other 3DQA competitors. The code is available at https://github.com/zzc-1998/GMS-3DQA. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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