2 citations · 4 across the 4 of their papers we have counts for
4 papers
An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction
Gang Qiao, Kaidong Hu, Seonghyeon Moon +4
Learning-based approaches to modeling crowd motion have become increasingly successful but require training and evaluation on large datasets, coupled with complex model selection a…
MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Prediction
Mihee Lee, Samuel S. Sohn, Seonghyeon Moon +3
Accurate long-term trajectory prediction in complex scenes, where multiple agents (e.g., pedestrians or vehicles) interact with each other and the environment while attempting to a…
Deep Crowd-Flow Prediction in Built Environments
Samuel S. Sohn, Seonghyeon Moon, Honglu Zhou +3
Predicting the behavior of crowds in complex environments is a key requirement in a multitude of application areas, including crowd and disaster management, architectural design, a…
Cognitive Agent Based Simulation Model For Improving Disaster Response Procedures
Rohit K. Dubey, Samuel S. Sohn, Christoph Hoelscher +1
In the event of a disaster, saving human lives is of utmost importance. For developing proper evacuation procedures and guidance systems, behavioural data on how people respond dur…