Pedestrian group pooling&unpooling and group hierarchy graph for group behavior modeling. Group-level latent vector sampling strategy to share the latent vector between group members. All models were trained and tested on Ubuntu 20.04 with Python 3.7 …

2022年7月20日 · In this paper, we present a novel architecture named GP-Graph which has collective group representations for effective pedestrian trajectory prediction in crowded environments, and is compatible with all types of existing approaches. A key idea of GP-Graph is to model both individual-wise and group-wise relations as graph representations.

This repository contains the code for unsupervised group estimation applied to the trajectory prediction models. Learns to assign each pedestrian into the most likely behavior group in unsupervised manner. To train our GPGraph-SGCN on the ETH and UCY datasets at once, we provide a bash script train.sh for a simplified execution.

In this paper, we present a novel architecture named GP-Graph which has collective group representations for effective pedestrian trajectory prediction in crowded environments, and is compatible with all types of existing approaches. A key idea of GP-Graph is to model both individual-wise and group-wise relations as graph representations.

2022年7月20日 · GP-Graph 的一个关键思想是将个体关系和组关系建模为图表示。 为此，GP-Graph 首先学习将每个行人分配到最可能的行为组中。 使用此分配信息，GP-Graph 然后将组内和组间交互形成为图，分别考虑群体内的人际关系和群体-群体关系。

2022年10月23日 · In this paper, we present a novel architecture named GP-Graph which has collective group representations for effective pedestrian trajectory prediction in crowded environments, and is compatible with all types of existing approaches. A key idea of GP-Graph is to model both individual-wise and group-wise relations as graph representations.

2024年11月1日 · GP-Graph is a model that combines Gaussian Process regression with graph neural networks for the prediction of pedestrian trajectories. It utilises graph representations to capture spatial dependencies and uncertainty modelling tech- niques for …

本文介绍了一种新颖的架构，称为gp图，它具有有效的集体群表示法来预测拥挤环境下人行路径，同时兼容所有现有方法。 GP-Graph模型了解了个体和群体之间的关系，通过图形表示来表征它们，为个人之间的关系和一组之间的关系建立了图形交互，并在这些交互 ...

GP-Graph is to model both individual-wise and group-wise relations as graph representations. To do this, GP-Graph first learns to assign each pedestrian into the most likely behavior group. Using this assignment in-formation, GP-Graph then forms both intra- and inter-group interactions as graphs, accounting for human-human relations within a ...

Genotype-phenotype maps in NetworkX.