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MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction.
Liu, Shaohua; Liu, Haibo; Wang, Yisu; Sun, Jingkai; Mao, Tianlu.
Affiliation
  • Liu S; School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Liu H; School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Wang Y; School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Sun J; School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Mao T; Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
Comput Intell Neurosci ; 2022: 4192367, 2022.
Article in En | MEDLINE | ID: mdl-35463224
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pedestrians Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Comput Intell Neurosci Journal subject: INFORMATICA MEDICA / NEUROLOGIA Year: 2022 Document type: Article Affiliation country: China Country of publication: Estados Unidos
Fulltext
Add to My VHL
Print
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pedestrians Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Comput Intell Neurosci Journal subject: INFORMATICA MEDICA / NEUROLOGIA Year: 2022 Document type: Article Affiliation country: China Country of publication: Estados Unidos