3 citations · 6 across the 4 of their papers we have counts for
4 papers
Toward Unsupervised 3D Point Cloud Anomaly Detection using Variational Autoencoder
Mana Masuda, Ryo Hachiuma, Ryo Fujii +2
In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. To the best of our knowledge, this is the first work to tackle the anomaly det…
Deep Selection: A Fully Supervised Camera Selection Network for Surgery Recordings
Ryo Hachiuma, Tomohiro Shimizu, Hideo Saito +2
Recording surgery in operating rooms is an essential task for education and evaluation of medical treatment. However, recording the desired targets, such as the surgery field, surg…
Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling
Ryo Hachiuma, Fumiaki Sato, Taiki Sekii
This paper simultaneously addresses three limitations associated with conventional skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the ta…
Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features
Fumiaki Sato, Ryo Hachiuma, Taiki Sekii
This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without abnormal samples, and…