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Non-Probability Sampling Network for Stochastic Human Trajectory Prediction
9 references·1 citing·22 second hop
Non-Probability Sampling Network for Stochastic Human Trajectory Prediction (2022)Non-Probability Sampling Network for Stoc…Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction (2020)Spatio-Temporal Graph Transfo…Recursive Social Behavior Graph for Trajectory Prediction (2020)Recursive Social Behavior Gra…STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction (2019)STGAT: Modeling Spatial-Tempo…SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction (2019)SR-LSTM: State Refinement for…Social Attention: Modeling Attention in Human Crowds (2018)Social Attention: Modeling At…Understanding pedestrian behaviors from stationary crowd groups (2015)Understanding pedestrian beha…Crowds by Example (2007)Crowds by ExampleSampling for qualitative research (1996)Sampling for qualitative rese…Social force model for pedestrian dynamics (1995)Social force model for pedest…Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction (2022)Learning Pedestrian Group Rep…Simulating dynamical features of escape panic (2000)Agent-based modeling: Methods and techniques for simulating human systems (2002)Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection (2018)Human Trajectory Forecasting in Crowds: A Deep Learning Perspective (2021)T HE F LOW OF H UMAN C ROWDS (2002)Continuum crowds (2006)THE DISCOVERY OF GROUNDED THEORY: STRATEGIES FOR QUALITATIVE RESEARCH. By Barney G. Glaser and Anselm L. Strauss. Chicago: Aldine Publishing Company, 1967. 271 pp. $6.75 (1968)The key informant technique (1996)Field Research: A Sourcebook and Field Manual (2003)‘Unsatisfactory Saturation’: a critical exploration of the notion of saturated sample sizes in qualitative research (2012)Sample Size in Qualitative Interview Studies (2015)Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period (2018)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)A System for the Notation of Proxemic Behavior1 (1963)Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions (2005)AST-GNN: An attention-based spatio-temporal graph neural network for Interaction-aware pedestrian trajectory prediction (2021)The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics (2010)Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches (2022)Synchronous Spatiotemporal Graph Transformer: A New Framework for Traffic Data Prediction (2022)
this work references cited by second hop

References

  • 1995Social force model for pedestrian dynamics7,112 cited
  • 1996Sampling for qualitative research4,755 cited
  • 2007Crowds by Example1,210 cited
  • 2019STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction712 cited
  • 2018Social Attention: Modeling Attention in Human Crowds710 cited
  • 2020Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction645 cited
  • 2019SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction592 cited
  • 2015Understanding pedestrian behaviors from stationary crowd groups248 cited
  • 2020Recursive Social Behavior Graph for Trajectory Prediction235 cited

Cited by

  • 2022Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction69 cited

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