all AI news
Beyond Average: Individualized Visual Scanpath Prediction
April 19, 2024, 4:45 a.m. | Xianyu Chen, Ming Jiang, Qi Zhao
cs.CV updates on arXiv.org arxiv.org
Abstract: Understanding how attention varies across individuals has significant scientific and societal impacts. However, existing visual scanpath models treat attention uniformly, neglecting individual differences. To bridge this gap, this paper focuses on individualized scanpath prediction (ISP), a new attention modeling task that aims to accurately predict how different individuals shift their attention in diverse visual tasks. It proposes an ISP method featuring three novel technical components: (1) an observer encoder to characterize and integrate an observer's …
abstract arxiv attention beyond bridge cs.cv differences gap however impacts modeling paper prediction scientific shift type understanding visual
More from arxiv.org / cs.CV updates on arXiv.org
TransRUPNet for Improved Polyp Segmentation
26 minutes ago |
arxiv.org
Learning to Complement with Multiple Humans
26 minutes ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Sr. VBI Developer II
@ Atos | Texas, US, 75093
Wealth Management - Data Analytics Intern/Co-op Fall 2024
@ Scotiabank | Toronto, ON, CA