Methods › Computer Vision › Trajectory Prediction Models › Social-STGCNN
Social-STGCNN
Introduced by Abduallah Mohamed et al. in Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Social-STGCNN is a method for human trajectory prediction. Pedestrian trajectories are not only influenced by the pedestrian itself but also by interaction with surrounding objects.
Papers archive 2025-07-28
4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information 23 Sep 2024 · 1 repository · arXiv:2409.15224
-
Learning the Pedestrian-Vehicle Interaction for Pedestrian Trajectory Prediction 10 Feb 2022 · 0 repositories · arXiv:2202.05334
-
Social-IWSTCNN: A Social Interaction-Weighted Spatio-Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios 26 May 2021 · 0 repositories · arXiv:2105.12436
-
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction 27 Feb 2020 · 3 repositories · arXiv:2002.11927Syntology ran 0 of 6 samples · 6 unverified
Tasks archive 2025-07-28
10 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections