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PoPPL: Pedestrian Trajectory Prediction by LSTM With Automatic Route Class Clustering
8 references·0 citing·29 second hop
PoPPL: Pedestrian Trajectory Prediction by LSTM With Automatic Route Class Clustering (2020)PoPPL: Pedestrian Trajectory Prediction b…Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection (2018)Soft + Hardwired attention: A…Social Attention: Modeling Attention in Human Crowds (2018)Social Attention: Modeling At…Modeling cooperative navigation in dense human crowds (2017)Modeling cooperative navigati…A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)A Dual-Stage Attention-Based …Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)Predicting the Next Location:…Understanding pedestrian behaviors from stationary crowd groups (2015)Understanding pedestrian beha…Universal Power Law Governing Pedestrian Interactions (2014)Universal Power Law Governing…Social force model for pedestrian dynamics (1995)Social force model for pedest…Simulating dynamical features of escape panic (2000)How simple rules determine pedestrian behavior and crowd disasters (2011)Empirical analysis of the lane formation process in bidirectional pedestrian flow (2016)Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches (2022)Agent-based modeling: Methods and techniques for simulating human systems (2002)SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction (2019)Human Trajectory Forecasting in Crowds: A Deep Learning Perspective (2021)Field Theory in Social Science (1952)Field Theory in Social Science (1953)The Statistics of Crowd Fluids (1971)Simulation of pedestrian dynamics using a two-dimensional cellular automaton (2001)Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions (2005)Friendship and mobility (2011)You Are Where You Go (2015)DeepMove (2018)A Survey on Deep Learning for Human Mobility (2021)Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network (2021)Context-Aware Trajectory Prediction (2018)STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction (2019)Distributed Representations, Simple Recurrent Networks, and Grammatical Structure (1991)Dynamic Covariance Models for Multivariate Financial Time Series (2013)ARIMA Models and the Box-Jenkins Methodology (2016)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)A System for the Notation of Proxemic Behavior1 (1963)Continuum crowds (2006)Crowds by Example (2007)Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction (2020)
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References

  • 1995Social force model for pedestrian dynamics7,112 cited
  • 2017A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction1,700 cited
  • 2016Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts1,023 cited
  • 2018Social Attention: Modeling Attention in Human Crowds710 cited
  • 2014Universal Power Law Governing Pedestrian Interactions392 cited
  • 2018Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection385 cited
  • 2015Understanding pedestrian behaviors from stationary crowd groups248 cited
  • 2017Modeling cooperative navigation in dense human crowds99 cited

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