most citedProbabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network

99 citations · 99 across the 1 of their papers we have counts for

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1 paper

cs.CV2020★ 99 cited

Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network

Stuart Eiffert, Kunming Li, Mao Shan +3

Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds. This problem becomes increasingly complex…