相关论文: No-Reference Point Cloud Quality Assessment via Do…

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 instrumental in facilitating immersive media applications,…

Three-dimensional (3D) point cloud, as an emerging visual media format, is increasingly favored by consumers as it can provide more realistic visual information than two-dimensional (2D) data. Similar to 2D plane images and videos, point…

Point cloud is one of the most widely used digital formats of 3D models, the visual quality of which is quite sensitive to distortions such as downsampling, noise, and compression. To tackle the challenge of point cloud quality assessment…

No-Reference Point Cloud Quality Assessment (NR-PCQA) still struggles with generalization, primarily due to the scarcity of annotated point cloud datasets. Since the Human Visual System (HVS) drives perceptual quality assessment…

The visual quality of point clouds has been greatly emphasized since the ever-increasing 3D vision applications are expected to provide cost-effective and high-quality experiences for users. Looking back on the development of point cloud…

With the rapid development of 3D vision, point cloud has become an increasingly popular 3D visual media content. Due to the irregular structure, point cloud has posed novel challenges to the related research, such as compression,…

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 knowledge in images, called the Distribution-Weighted…

While no-reference point cloud quality assessment (NR-PCQA) approaches have achieved significant progress over the past decade, their performance often degrades substantially when a distribution gap exists between the training (source…

To improve the viewer's Quality of Experience (QoE) and optimize computer graphics applications, 3D model quality assessment (3D-QA) has become an important task in the multimedia area. Point cloud and mesh are the two most widely used…

No-Reference Point Cloud Quality Assessment (NR-PCQA) is critical for evaluating 3D content in real-world applications where reference models are unavailable.

With the rapid development of 3D vision applications based on point clouds, point cloud quality assessment(PCQA) is becoming an important research topic. However, the prior PCQA methods ignore the effect of local quality variance across…

Full-reference (FR) point cloud quality assessment (PCQA) has achieved impressive progress in recent years. However, in many cases, obtaining the reference point clouds is difficult, so no-reference (NR) metrics have become a research…

With the wide applications of colored point cloud in many fields, point cloud perceptual quality assessment plays a vital role in the visual communication systems owing to the existence of quality degradations introduced in various stages.…

With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media. Besides several distortions that could affect the 3D content spanning from acquisition to…

Deep learning-based quality assessments have significantly enhanced perceptual multimedia quality assessment, however it is still in the early stages for 3D visual data such as 3D point clouds (PCs). Due to the high volume of 3D-PCs, such…

Point cloud is one of the most widely used digital representation formats for three-dimensional (3D) contents, the visual quality of which may suffer from noise and geometric shift distortions during the production procedure as well as…

During the compression, transmission, and rendering of point clouds, various artifacts are introduced, affecting the quality perceived by the end user. However, evaluating the impact of these distortions on the overall quality is a…

The evolution of point cloud processing algorithms necessitates an accurate assessment for their quality. Previous works consistently regard point cloud quality assessment (PCQA) as a MOS regression problem and devise a deterministic…

Large Multimodal Models (LMMs) have recently enabled considerable advances in the realm of image and video quality assessment, but this progress has yet to be fully explored in the domain of 3D assets. We are interested in using these…

Point clouds are widely used in 3D content representation and have various applications in multimedia. However, compression and simplification processes inevitably result in the loss of quality-aware information under storage and bandwidth…