Group and Crowd Behavior for Computer Vision

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Stochastic Prediction of Multi-Agent Interactions from Partial Observations (2019, methodology): “…the agents is assumed to be known (e.g., using fully connected graphs or using a sparse graph derived from spatial proximity), as in the social LSTM (Alahi et al., 2016) and the social GAN (Gupta et al., 2018), or methods based on inverse optimal control (Kitani et al., 2017; Lee et al., 2017).”
Intelligent video surveillance: a review through deep learning techniques for crowd analysis (2019, methodology): “Figure 6 represents a comparison of detection performance which is conducted by different methods [80].”
Human motion trajectory prediction: a survey (2019, background): “Murino et al. (2017) discuss group and crowd motion analysis as a multidisciplinary problem that combines insights from the social sciences with concepts from computer vision and pattern recognition.”