A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.
Social lstm: Human trajectory prediction in crowded spaces,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Extends Social-STGCNN with CVAE for multimodal trajectory prediction and reports moderate gains plus better diversity on ETH/UCY benchmarks and robot data.
citing papers explorer
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Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.
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On Improving Multimodal Pedestrian Trajectory Prediction with CVAE: A Study on Benchmark and Robot Data
Extends Social-STGCNN with CVAE for multimodal trajectory prediction and reports moderate gains plus better diversity on ETH/UCY benchmarks and robot data.