Tomoaki Konno — accepted AI-conference papers

2025

Full-Reference Point Cloud Quality Assessment with Multimodal Large Language Models

Ryosuke Watanabe, Tomoaki Konno, Hiroshi Sankoh, Bryan Tanaka, Tatsuya Kobayashi

ICASSP 2025accepted

Point cloud quality frequently degrades during various processes, such as scanning, compression, and transmission. Hence, reliable Point Cloud Quality Assessment (PCQA) methods are essential for detecting and mitigating the degradation in 3D applications. This paper proposes an accurate full-referen…

Cited by 0 Source ↗Scholar ↗

2019

Fast Free-viewpoint Video Synthesis Algorithm for Sports Scenes

Jun Chen, Ryosuke Watanabe, Keisuke Nonaka, Tomoaki Konno, Hiroshi Sankoh, Sei Naito

IROS 2019poster

In this paper, we report on a parallel free-viewpoint video synthesis algorithm that can efficiently reconstruct a high-quality 3D scene representation of sports scenes. The proposed method focuses on a scene that is captured by multiple synchronized cameras featuring wide-baselines. The following s…

Cited by 21 Source ↗Scholar ↗