Abstract
Point clouds represent one of the prevalent formats for 3D content. Distortions introduced at various stages in the point cloud processing pipeline affect the visual quality, altering their geometric composition, texture information, or both. Understanding and quantifying the impact of the distortion domain on visual quality is vital to driving rate optimization and guiding post-processing steps to improve the quality of experience. In this paper, we propose a multi-task guided multi-modality no reference metric (M3-Unity), which utilizes 4 types of modalities across attributes and dimensionalities to represent point clouds. An attention mechanism establishes inter/intra associations among 3D/2D patches, which can complement each other, yielding local and global features, to fit the highly nonlinear property of the human vision system. A multi-task decoder involving distortion type classification selects the best association among 4 modalities, aiding the regression task and enabling the in-depth analysis of the interplay between geometrical and textural distortions. Furthermore, our framework design and attention strategy enable us to measure the impact of individual attributes and their combinations, providing insights into how these associations contribute particularly in relation to distortion type. Extensive experimental results on 4 datasets consistently outperform the state-of-the-art metrics by a large margin.
Original language | English |
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Title of host publication | MM '24 |
Subtitle of host publication | Proceedings of the 32nd ACM International Conference on Multimedia |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery (ACM) |
Pages | 7813-7822 |
Number of pages | 10 |
ISBN (Electronic) | 979-8-4007-0686-8 |
DOIs | |
Publication status | Published - 2024 |
Event | 32nd ACM International Conference on Multimedia, MM 2024 - Melbourne, Australia Duration: 28 Oct 2024 → 1 Nov 2024 https://2024.acmmm.org/ |
Conference
Conference | 32nd ACM International Conference on Multimedia, MM 2024 |
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Abbreviated title | MM 2024 |
Country/Territory | Australia |
City | Melbourne |
Period | 28/10/24 → 1/11/24 |
Internet address |
Keywords
- geometry and texture
- multi-modal
- multi-task
- objective quality assessment
- point cloud