@inproceedings{
zhou2024deciphering,
title={Deciphering Perceptual Quality in Colored Point Cloud: Prioritizing Geometry or Texture Distortion?},
author={Xuemei Zhou and Irene Viola and Yunlu Chen and Jiahuan Pei and Pablo Cesar},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=YE7G4Soi7k}
}
Point cloud contents represent one of the prevalent formats for 3D representations. 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 postprocessing
steps to improve the overall quality of experience. In this paper, we propose a multi-task guided multi-modality no reference
metric for measuring the quality of colored point clouds (M3-Unity), which utilizes 4 types of modalities across different attributes and
dimensionalities to represent point clouds. An attention mechanism establishes inter/intra associations among 3D/2D patches,
which can complement each other, yielding both 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 combination among 4 modalities based on the
specific distortion type, 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. Experimental
results demonstrate that our method effectively predicts the visual quality of point clouds, achieving state-of-the-art performance on
four benchmark datasets. The code will be released.
Deciphering Perceptual Quality in Colored Point Cloud: Prioritizing Geometry or Texture Distortion?
Xuemei Zhou Irene Viola Yunlu Chen Jiahuan Pei Pablo Cesar