3 citations · 3 across the 4 of their papers we have counts for
4 papers
Data-driven Head Motion Generation through Natural Gaze-Head Coordination
Xiaohan Liu, Yilin Wen, Yusuke Sugano
We present the first data-driven approach to model temporal gaze-head coordination from large-scale in-the-wild facial videos. To obtain training data for generalizable learning, w…
TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices
Wataru Kawabe, Hiroto Fukuda, Akihisa Shitara +2
We introduce TofuML, an interactive system designed to make machine learning (ML) concepts more accessible and engaging for non-expert users. Unlike conventional GUI-based systems,…
DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users
Wataru Kawabe, Yusuke Sugano
Machine learning (ML) models have significantly impacted various domains in our everyday lives. While large language models (LLMs) offer intuitive interfaces and versatility, task-…
Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation
Mingtao Yue, Tomomi Sayuda, Miles Pennington +1
Appearance-based gaze estimation, which uses only a regular camera to estimate human gaze, is important in various application fields. While the technique faces data bias issues, d…