Non-Autoregressive Transformer Based Ego-Motion Independent Pedestrian Trajectory Prediction on Egocentric View

Predicting the future trajectories of surrounding pedestrians is undoubtedly one of the most essential but challenging tasks for safe urban autonomous driving. Despite this importance, there has been limited research conducted on the egocentric view from easy-to-access vehicle-mounted cameras for au...

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Bibliographic Details
Published in:	IEEE access Vol. 11; pp. 104554 - 104567
Main Authors:	Kim, Yujin, Seo, Eunbin, Noh, Chiyun, Yi, Kyongsu
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	attention mechanism Autonomous driving autonomous vehicle Autonomous vehicles Cameras Datasets egocentric view Modules Motion compensation Motion planning non-autoregressive transformer pedestrian trajectory prediction Pedestrians Predictions Predictive models Risk assessment Trajectories Trajectory Transformers Visualization
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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