HCSG combines geometric forecasting of human pose and trajectory with VLM-generated semantic descriptions of intentions, fused into a topological map with a social distance loss, yielding 14% higher success rate and 34% lower collision rate on the HA-VLNCE benchmark.
Holistic lstm for pedestrian trajectory prediction,
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
A MAPE-K-orchestrated Kubernetes edge system for neural-network human-mobility prediction in robotics reports improved service quality over static setups by monitoring response time and power.
citing papers explorer
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HCSG: Human-Centric Semantic-Geometric Reasoning for Vision-Language Navigation
HCSG combines geometric forecasting of human pose and trajectory with VLM-generated semantic descriptions of intentions, fused into a topological map with a social distance loss, yielding 14% higher success rate and 34% lower collision rate on the HA-VLNCE benchmark.
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Self-adaptive Multi-Access Edge Architectures: A Robotics Case
A MAPE-K-orchestrated Kubernetes edge system for neural-network human-mobility prediction in robotics reports improved service quality over static setups by monitoring response time and power.