activity
20172023
most citedSCP: Spherical-Coordinate-based Learned Point Cloud Compression

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

SCP: Spherical-Coordinate-based Learned Point Cloud Compression

Ao Luo, Linxin Song, Keisuke Nonaka +4

In recent years, the task of learned point cloud compression has gained prominence. An important type of point cloud, the spinning LiDAR point cloud, is generated by spinning LiDAR…

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…

eess.IV2022

Fractional Motion Estimation for Point Cloud Compression

Haoran Hong, Eduardo Pavez, Antonio Ortega +2

Motivated by the success of fractional pixel motion in video coding, we explore the design of motion estimation with fractional-voxel resolution for compression of color attributes…

cs.MM2019

A Robust Billboard-based Free-viewpoint Video Synthesizing Algorithm for Sports Scenes

Jun Chen, Ryosuke Watanabe, Keisuke Nonaka +3

We present a billboard-based free-viewpoint video synthesizing algorithm for sports scenes that can robustly reconstruct and render a high-fidelity billboard model for each object,…

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…