Multi-agent Trajectory Prediction on 4-agent scenarios inferred goals benchmark leaderboard · SOTA2 Research

Multi-agent Trajectory Prediction on 4-agent scenarios inferred goals

0.1816ADE (m)PSN-Partial

Evaluation Results

Method	Links
PSN-Partial2025.04		0.1816	0.2674	0.9856	2
PSN-Full2025.04		0.1834	0.2785	0.9901	1.66
PSN-Full2025.04		0.1839	0.2749	0.9901	2
Cost Evolution2025.04		0.1861	0.2661	0.98	2
PSN-Partial2025.04		0.1876	0.2745	0.9856	1.87
kNNs2025.04		0.1884	0.2802	0.9887	2
BF2025.04		0.1899	0.2812	0.9917	2
CBF2025.04		0.1921	0.2843	0.9931	2
Gradient2025.04		0.1925	0.2817	0.9885	2
Hessian2025.04		0.1938	0.2851	0.9915	2
Distance2025.04		0.204	0.2985	0.9949	1.2
PSN-Full2025.04		0.2989	0.5075	0.9903	1.66
PSN-Full2025.04		0.3003	0.5037	0.9904	2
Cost Evolution2025.04		0.3096	0.5081	0.9806	2
kNNs2025.04		0.3118	0.5211	0.9899	2
Gradient2025.04		0.3121	0.5177	0.9791	2
PSN-Partial2025.04		0.3127	0.5139	0.9869	2
BF2025.04		0.3127	0.5223	0.9898	2
CBF2025.04		0.3149	0.5234	0.9922	2
PSN-Partial2025.04		0.315	0.5156	0.987	1.88
Hessian2025.04		0.3157	0.5211	0.9912	2
Distance2025.04		0.32	0.5231	0.9941	2