4 papers
Unsupervised 3D Human Pose Estimation via Conditional Multi-view Ancestral Sampling
Ryohei Goto, Takuya Fujihashi, Shunsuke Saruwatari +1
We propose a method of estimating a 3D human pose from a single view without 3D supervision. The key to our method is to leverage the 2D diffusion priors of motion diffusion models…
Range Image-Based Implicit Neural Compression for LiDAR Point Clouds
Akihiro Kuwabara, Sorachi Kato, Toshiaki Koike-Akino +1
This paper presents a novel scheme to efficiently compress Light Detection and Ranging~(LiDAR) point clouds, enabling high-precision 3D scene archives, and such archives pave the w…
RAPTR: Radar-based 3D Pose Estimation using Transformer
Sorachi Kato, Ryoma Yataka, Pu Perry Wang +3
Radar-based indoor 3D human pose estimation typically relied on fine-grained 3D keypoint labels, which are costly to obtain especially in complex indoor settings involving clutter,…
Quantum Implicit Neural Compression
Takuya Fujihashi, Toshiaki Koike-Akino
Signal compression based on implicit neural representation (INR) is an emerging technique to represent multimedia signals with a small number of bits. While INR-based signal compre…