99 citations · 99 across the 3 of their papers we have counts for
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cs.CV2020
Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases
Kunming Li, Stuart Eiffert, Mao Shan +3
Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion both accurately and with minimal delay. Understanding the uncert…
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…
cs.CV2018
Adversarial Noise Layer: Regularize Neural Network By Adding Noise
Zhonghui You, Jinmian Ye, Kunming Li +2
In this paper, we introduce a novel regularization method called Adversarial Noise Layer (ANL) and its efficient version called Class Adversarial Noise Layer (CANL), which are able…