MC-Risk linearly composes motorized-agent, VRU, and road-penalty fields into a bird's-eye-view risk grid that achieves superior localization and early detection on RiskBench while serving as an MPC cost for risk-aware planning.
Social gan: Socially acceptable trajectories with generative adversarial networks
2 Pith papers cite this work. Polarity classification is still indexing.
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TacticGen generates realistic, adaptable football tactics via a multi-agent diffusion transformer trained on 3.3M events and 100M frames, supporting rule-, language-, or model-based guidance at inference time.
citing papers explorer
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MC-Risk: Multi-Component Risk Fields for Risk Identification and Motion Planning
MC-Risk linearly composes motorized-agent, VRU, and road-penalty fields into a bird's-eye-view risk grid that achieves superior localization and early detection on RiskBench while serving as an MPC cost for risk-aware planning.
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TacticGen: Grounding Adaptable and Scalable Generation of Football Tactics
TacticGen generates realistic, adaptable football tactics via a multi-agent diffusion transformer trained on 3.3M events and 100M frames, supporting rule-, language-, or model-based guidance at inference time.