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20182026
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cs.CV2024

Full reference point cloud quality assessment using support vector regression

Ryosuke Watanabe, Shashank N. Sridhara, Haoran Hong +4

Point clouds are a general format for representing realistic 3D objects in diverse 3D applications. Since point clouds have large data sizes, developing efficient point cloud compr…

cs.CV2024

Full-reference Point Cloud Quality Assessment Using Spectral Graph Wavelets

Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez +2

Point clouds in 3D applications frequently experience quality degradation during processing, e.g., scanning and compression. Reliable point cloud quality assessment (PCQA) is impor…

cs.CV2024

Fast graph-based denoising for point cloud color information

Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez +2

Point clouds are utilized in various 3D applications such as cross-reality (XR) and realistic 3D displays. In some applications, e.g., for live streaming using a 3D point cloud, re…

cs.CV2022

Motion estimation and filtered prediction for dynamic point cloud attribute compression

Haoran Hong, Eduardo Pavez, Antonio Ortega +2

In point cloud compression, exploiting temporal redundancy for inter predictive coding is challenging because of the irregular geometry. This paper proposes an efficient block-base…

cs.CV2019

A Fast Free-viewpoint Video Synthesis Algorithm for Sports Scenes

Jun Chen, Ryosuke Watanabe, Keisuke Nonaka +3

In this paper, we report on a parallel freeviewpoint video synthesis algorithm that can efficiently reconstruct a high-quality 3D scene representation of sports scenes. The propose…

cs.CV2018

Efficient Parallel Connected Components Labeling with a Coarse-to-fine Strategy

Jun Chen, Keisuke Nonaka, Ryosuke Watanabe +3

This paper proposes a new parallel approach to solve connected components on a 2D binary image implemented with CUDA. We employ the following strategies to accelerate neighborhood…