Seonghyeon Moon

About Seonghyeon Moon

Seonghyeon Moon, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Rutgers, The State University of New Jersey, specializes in the field of Crowd Simulation and Prediction, Computer Vision, Computer Graphics, Reinforcement learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

On the Equivalency, Substitutability, and Flexibility of Synthetic Data

Msi: maximize support-set information for few-shot segmentation

The role of latent representations for design space exploration of floorplans

Learning from Synthetic Human Group Activities

A Multiscale Geospatial Dataset and an Interactive Visualization Dashboard for Computational Epidemiology and Open Scientific Research

An information-theoretic approach for estimating scenario generalization in crowd motion prediction

Hm: Hybrid masking for few-shot segmentation

A2X: An end-to-end framework for assessing agent and environment interactions in multimodal human trajectory prediction

Seonghyeon Moon Information

University

Position

___

Citations(all)

133

Citations(since 2020)

133

Cited By

22

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Seonghyeon Moon Skills & Research Interests

Crowd Simulation and Prediction

Computer Vision

Computer Graphics

Reinforcement learning

Top articles of Seonghyeon Moon

On the Equivalency, Substitutability, and Flexibility of Synthetic Data

arXiv preprint arXiv:2403.16244

2024/3/24

Msi: maximize support-set information for few-shot segmentation

2023

The role of latent representations for design space exploration of floorplans

Simulation

2023/11

Learning from Synthetic Human Group Activities

arXiv preprint arXiv:2306.16772

2023/6/29

A Multiscale Geospatial Dataset and an Interactive Visualization Dashboard for Computational Epidemiology and Open Scientific Research

IEEE Computer Graphics and Applications

2022/12/19

An information-theoretic approach for estimating scenario generalization in crowd motion prediction

arXiv preprint arXiv:2211.00817

2022/11/2

Hm: Hybrid masking for few-shot segmentation

2022/10/20

A2X: An end-to-end framework for assessing agent and environment interactions in multimodal human trajectory prediction

Computers & Graphics

2022/8/1

Harnessing fourier isovists and geodesic interaction for long-term crowd flow prediction

2022

Muse-vae: Multi-scale vae for environment-aware long term trajectory prediction

2022

A2x: An agent and environment interaction benchmark for multimodal human trajectory prediction

2021/11/10

Deep integration of physical humanoid control and crowd navigation

2020/10/16

JOIN: an integrated platform for joint simulation of occupant-building interactions

Architectural Science Review

2020/7/3

Laying the foundations of deep long-term crowd flow prediction

Proceedings of the European Conference on Computer Vision (ECCV)

2020

See List of Professors in Seonghyeon Moon University(Rutgers, The State University of New Jersey)

Co-Authors

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