6 citations · 23 across the 18 of their papers we have counts for
7 papers · 1 filter
RealTraj: Towards Real-World Pedestrian Trajectory Forecasting
Ryo Fujii, Hideo Saito, Ryo Hachiuma
This paper jointly addresses three key limitations in conventional pedestrian trajectory forecasting: pedestrian perception errors, real-world data collection costs, and person ID…
Advanced POD-Based Performance Evaluation of Classifiers Applied to Human Driver Lane Changing Prediction
Zahra Rastin, Dirk Söffker
Machine learning (ML) classifiers serve as essential tools facilitating classification and prediction across various domains. The performance of these algorithms should be known to…
CrowdMAC: Masked Crowd Density Completion for Robust Crowd Density Forecasting
Ryo Fujii, Ryo Hachiuma, Hideo Saito
A crowd density forecasting task aims to predict how the crowd density map will change in the future from observed past crowd density maps. However, the past crowd density maps are…
EgoSurgery-Tool: A Dataset of Surgical Tool and Hand Detection from Egocentric Open Surgery Videos
Ryo Fujii, Hideo Saito, Hiroki Kajita
Surgical tool detection is a fundamental task for understanding egocentric open surgery videos. However, detecting surgical tools presents significant challenges due to their highl…
Multimodal Cross-Domain Few-Shot Learning for Egocentric Action Recognition
Masashi Hatano, Ryo Hachiuma, Ryo Fujii +1
We address a novel cross-domain few-shot learning task (CD-FSL) with multimodal input and unlabeled target data for egocentric action recognition. This paper simultaneously tackles…
EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery Videos
Ryo Fujii, Masashi Hatano, Hideo Saito +1
Surgical phase recognition has gained significant attention due to its potential to offer solutions to numerous demands of the modern operating room. However, most existing methods…
Weakly Semi-supervised Tool Detection in Minimally Invasive Surgery Videos
Ryo Fujii, Ryo Hachiuma, Hideo Saito
Surgical tool detection is essential for analyzing and evaluating minimally invasive surgery videos. Current approaches are mostly based on supervised methods that require large, f…