6 citations · 6 across the 10 of their papers we have counts for
10 papers
Motion Estimation Techniques for Volumetric Video Attribute Compression
Haoran Hong, Eduardo Pavez, Antonio Ortega +2
Point cloud compression relies on techniques to compress both geometry and attributes. Motion-based approaches for dynamic solid point cloud geometry compression within the geometr…
Graph-based Scalable Sampling of 3D Point Cloud Attributes
Shashank N. Sridhara, Eduardo Pavez, Ajinkya Jayawant +3
3D Point clouds (PCs) are commonly used to represent 3D scenes. They can have millions of points, making subsequent downstream tasks such as compression and streaming computational…
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…
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…
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…
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…