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20222025
most citedHuman Trajectory Prediction via Neural Social Physics

5 citations · 8 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review

Jiangbei Yue, He Wang

Crowd behaviour analysis is essential to numerous real-world applications, such as public safety and urban planning, and therefore has been studied for decades. In the last decade…

cs.CV2025

3D Student Splatting and Scooping

Jialin Zhu, Jiangbei Yue, Feixiang He +1

Recently, 3D Gaussian Splatting (3DGS) provides a new framework for novel view synthesis, and has spiked a new wave of research in neural rendering and related applications. As 3DG…

cs.CV2025

Learning Extremely High Density Crowds as Active Matters

Feixiang He, Jiangbei Yue, Jialin Zhu +4

Video-based high-density crowd analysis and prediction has been a long-standing topic in computer vision. It is notoriously difficult due to, but not limited to, the lack of high-q…

cs.CV2024

Human Motion Prediction under Unexpected Perturbation

Jiangbei Yue, Baiyi Li, Julien Pettré +2

We investigate a new task in human motion prediction, which is predicting motions under unexpected physical perturbation potentially involving multiple people. Compared with existi…

cs.CV2023★ 3 cited

Human Trajectory Forecasting with Explainable Behavioral Uncertainty

Jiangbei Yue, Dinesh Manocha, He Wang

Human trajectory forecasting helps to understand and predict human behaviors, enabling applications from social robots to self-driving cars, and therefore has been heavily investig…

cs.CV2022★ 5 cited

Human Trajectory Prediction via Neural Social Physics

Jiangbei Yue, Dinesh Manocha, He Wang

Trajectory prediction has been widely pursued in many fields, and many model-based and model-free methods have been explored. The former include rule-based, geometric or optimizati…