List your company

Trajectory Prediction on ETH-UCY (Scene-wise Evaluation)

0.18Average ADE (20)AGMA
0.13080.46290.7951.1271Mar 25, 2021Jan 15, 2022Nov 7, 2022Aug 30, 2023Jun 21, 2024Apr 13, 2025Feb 4, 2026

Evaluation results

MethodLinks
AGMAVenue=Ours2026.020.18——————————————————0.240.350.10.150.250.440.170.290.140.230.29——————————————
Trajectron++K (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.19——————————————————0.390.830.120.210.20.440.150.330.110.250.41——————————————
NMRFVenue=ICLR’252026.020.19——————————————————0.260.370.110.170.280.490.170.30.140.250.32——————————————
Trajectron++2022.030.2————————————————————————————0.44——————————————
MoFlowNFE=1002025.030.2——————————————————0.390.550.110.170.220.390.170.290.120.220.32——————————————
MoFlow2025.030.2——————————————————0.40.570.110.170.230.390.150.260.120.220.32——————————————
VIKTVenue=TITS’232026.020.2——————————————————0.30.510.130.250.230.510.210.440.140.30.4——————————————
SocialCircleVenue=CVPR’242026.020.2——————————————————0.270.420.130.160.290.510.190.330.140.250.33——————————————
MID2025.030.21——————————————————0.390.660.130.220.220.450.170.30.130.270.38——————————————
TUTR2025.030.21——————————————————0.40.610.110.180.230.420.180.340.130.250.36——————————————
EqMotion2025.030.21——————————————————0.40.610.120.180.230.430.180.320.130.230.35——————————————
EigenTraj2025.030.21——————————————————0.360.530.120.190.240.340.190.330.140.240.34——————————————
LED2025.030.21——————————————————0.390.580.110.170.260.440.180.260.130.220.33——————————————
SingularTraj2025.030.21——————————————————0.350.420.130.190.250.440.190.320.150.250.32——————————————
IMLENFE=12025.030.21——————————————————0.40.610.120.180.240.440.170.310.130.240.36——————————————
MID2025.030.21——————————————————0.390.660.130.220.220.450.170.30.130.270.38——————————————
TUTR2025.030.21——————————————————0.40.610.110.180.230.420.180.340.130.250.36——————————————
EqMotion2025.030.21——————————————————0.40.610.120.180.230.430.180.320.130.230.35——————————————
EigenTraj2025.030.21——————————————————0.360.530.120.190.240.340.190.330.140.240.34——————————————
LED*Model Type=student model LED initializer2025.030.21——————————————————0.390.580.110.170.260.440.180.260.130.220.33——————————————
SingularTraj2025.030.21——————————————————0.350.420.130.190.250.440.190.320.150.250.32——————————————
IMLEDescription=IMLE distillation method2025.030.21——————————————————0.40.580.120.180.230.390.160.260.130.220.33——————————————
EigenTrajVenue=ICCV’232026.020.21——————————————————0.360.530.120.190.240.340.190.330.140.240.33——————————————
SingularTrajVenue=CVPR’242026.020.21——————————————————0.350.420.130.190.250.440.190.320.150.250.32——————————————
MGFVenue=NIPS’242026.020.21——————————————————0.390.590.130.20.210.390.170.290.140.240.34——————————————
MoFlowVenue=CVPR’252026.020.21——————————————————0.40.570.120.180.230.40.170.30.130.230.34——————————————
EqMotionSampling Protocol=Best-of-202024.010.21——————————————————0.40.610.120.180.230.430.180.320.130.230.35——————————————
LEDSampling Protocol=Best-of-202024.010.21——————————————————0.390.580.110.170.260.440.180.260.130.220.33——————————————
IMLESampling Protocol=Best-of-202024.010.21——————————————————0.40.580.120.180.230.390.160.260.130.220.33——————————————
Hyper-STTNSampling Protocol=Best-of-202024.010.21——————————————————0.350.570.140.180.230.410.180.280.150.220.33——————————————
AgentFormerK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.23——————————————————0.450.750.140.220.250.450.180.30.140.240.39——————————————
TUTRVenue=ICCV’232026.020.23——————————————————0.450.670.140.20.240.440.190.360.150.280.39——————————————
MemoNet2022.030.24————————————————————————————0.43——————————————
Agentformer2022.030.25————————————————————————————0.45——————————————
GroupNet2025.030.25——————————————————0.460.730.150.250.260.490.210.390.170.330.44——————————————
GroupNet2025.030.25——————————————————0.460.730.150.250.260.490.210.390.170.330.44——————————————
GP-GraphVenue=ECCV’222026.020.25——————————————————0.430.630.180.30.250.480.230.450.180.350.44——————————————
GroupNetSampling Protocol=Best-of-202024.010.25——————————————————0.460.730.150.250.260.490.210.390.170.330.44——————————————
STARK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.26——————————————————0.360.650.170.360.310.620.260.550.220.460.53——————————————
STARSampling Protocol=Best-of-202024.010.26——————————————————0.360.650.170.360.310.620.260.550.220.460.53——————————————
PECNetK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.29——————————————————0.540.870.180.240.350.60.220.390.170.30.48——————————————
HGNN (ablation)Sampling Protocol=Best-of-202024.010.29——————————————————0.420.730.210.320.30.530.280.530.230.280.48——————————————
Trajectron++Sampling Protocol=Best-of-202024.010.3——————————————————0.611.020.190.280.30.540.240.420.180.320.51——————————————
Transformer-TFK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.31——————————————————0.611.120.180.30.350.650.220.380.170.320.55——————————————
STAR2022.030.31————————————————————————————0.62——————————————
STTN (ablation)Sampling Protocol=Best-of-202024.010.31——————————————————0.520.750.210.250.250.430.310.390.250.330.43——————————————
PECNETVenue=ECCV’202026.020.33——————————————————0.641.130.220.380.350.570.250.450.180.310.57——————————————
Social-ImplicitSampling Protocol=Best-of-202024.010.33——————————————————0.611.080.330.630.521.110.320.660.430.850.67——————————————
Transformer-TF2022.030.35————————————————————————————0.65——————————————
PECNet2022.030.35————————————————————————————0.6——————————————
STAR2022.030.36————————————————————————————0.65——————————————
MANTRA2022.030.37————————————————————————————0.81——————————————
Trajectron++Venue=ECCV’202026.020.37——————————————————0.611.030.320.550.370.70.290.530.250.450.65——————————————
Trajectron++2022.030.39————————————————————————————0.83——————————————
MemoNet2022.030.4————————————————————————————0.61——————————————
Agentformer2022.030.45————————————————————————————0.75——————————————
MANTRA2022.030.48————————————————————————————0.88——————————————
STGAT2022.030.52————————————————————————————1.1——————————————
NMMP2022.030.52————————————————————————————1.11——————————————
SoPhieK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.54——————————————————0.71.430.761.670.541.240.30.630.380.781.15——————————————
PECNet2022.030.54————————————————————————————0.87——————————————
SGANK (Number of samples)=20, Evaluation Protocol=leave-one-out2021.030.58——————————————————0.811.520.721.610.61.260.340.690.420.841.18——————————————
NMMP2022.030.61————————————————————————————1.08——————————————
Transformer-TF2022.030.61————————————————————————————1.12——————————————
Social GANSampling Protocol=Best-of-202024.010.61——————————————————0.871.620.671.370.761.520.350.680.420.841.21——————————————
STGAT2022.030.65————————————————————————————1.12——————————————
Social-GAN2022.030.76————————————————————————————1.52——————————————
Social-GAN2022.030.87————————————————————————————1.62——————————————
Social AttentionSampling Protocol=Best-of-202024.011.41——————————————————1.392.392.512.911.252.541.012.170.881.752.35——————————————
AgentFormerK=20, Map Information=false2022.03———————0.450.750.140.220.250.450.180.30.140.240.230.39—————————————————————————
AutoBotsDeterministic=true2023.12———————0.931.870.320.650.541.150.420.910.340.770.511.07—————————————————————————
AutoBots + RankingDeterministic=true2023.12———————0.91.780.30.560.531.120.410.890.320.70.491.01—————————————————————————
BitTP-ActivationQuantization Strategy=8-bit activations, Backbone=T5-small, Batch Size=1282026.05———————2.894.861.162.021.362.472.43.671.42.551.843.12———————————————————————1.492.5
BitTP-BothQuantization Strategy=Weights & Activations, Backbone=T5-small, Batch Size=1282026.05———————1.731.410.840.781.131.111.661.440.970.941.271.13———————————————————————0.920.51
BitTP-WeightQuantization Strategy=1.58-bit weights, Backbone=T5-small, Batch Size=1282026.05———————0.460.620.170.270.420.80.230.40.220.390.30.49———————————————————————-0.05-0.13
CGNSK=20, Error Unit=meters2020.06———————0.621.40.70.930.481.220.320.590.350.710.490.97—————————————————————————
CGNSK=20, Map Information=false2022.03———————0.621.40.70.930.481.220.320.590.350.710.490.97—————————————————————————
D-LSTMDeterministic=true2023.12———————1.052.10.460.930.571.250.40.90.370.890.571.21—————————————————————————
Expert-GoalsK=20, Map Information=false2022.03———————0.370.650.110.150.20.440.150.310.120.250.190.36—————————————————————————
FvTrajEvaluation Mode=Deterministic2021.03——————————————————————————————0.621.230.531.10.571.190.420.890.380.790.51.04——
GOAL-GANK=20, Error Unit=meters2020.06———————0.591.180.190.350.61.190.430.870.320.650.430.85—————————————————————————
GOAL-GANK=20, Map Information=true2022.03———————0.591.180.190.350.61.190.430.870.320.650.430.85—————————————————————————
IntrovertK=20, Map Information=true2022.03———————0.420.70.110.170.20.320.160.270.160.250.210.34—————————————————————————
LB-EBM2021.04—2.34-1.160.54-0.17-1.58-0.01—————————————————————————————————————
LB-EBMK=20, Map Information=false2022.03———————0.30.520.130.20.270.520.20.370.150.290.210.38—————————————————————————
LMTraj-SUPImplementation Source=Original paper reported2026.05———————0.410.510.120.160.220.340.20.320.170.270.220.32—————————————————————————
LMTraj-SUPImplementation Source=Backbone implementation, Precision=BF162026.05———————0.560.820.190.350.490.980.260.460.260.50.350.62———————————————————————00
LMTraj-SUP-int4Quantization Strategy=int42026.05———————0.470.710.20.360.490.970.250.440.280.540.340.6———————————————————————-0.010.02
LMTraj-SUP-int8Quantization Strategy=int82026.05———————0.470.670.190.350.490.980.260.460.260.490.340.59———————————————————————-0.01-0.03
MANTRAK=20, Error Unit=meters2020.06———————0.480.880.170.330.370.810.270.580.30.670.320.65—————————————————————————
MANTRAK=20, Map Information=false2022.03———————0.480.880.170.330.370.810.270.580.30.670.320.65—————————————————————————
MATFK=20, Error Unit=meters2020.06———————1.011.750.430.80.440.910.260.450.260.570.480.9—————————————————————————
MATFEvaluation Mode=Deterministic2021.03——————————————————————————————1.332.490.510.950.561.190.440.930.340.730.641.26——
MATFK=20, Map Information=false2022.03———————1.011.750.430.80.440.910.260.450.260.570.480.9—————————————————————————
MIDImplementation Source=Original paper reported2026.05———————0.570.930.210.330.290.550.280.50.20.370.310.54—————————————————————————
NextK=20, Map Information=true2022.03———————0.731.650.30.590.61.270.380.810.310.680.461—————————————————————————
NSP-SFMultra-sampling=true, samples per step=20, reporting=overall minimal error2022.07———————0.070.090.030.070.030.040.020.040.020.040.030.06—————————————————————————
ORCADeterministic=true2023.12———————2.273.441.031.541.292.0790.971.60.871.451.282.02—————————————————————————
PCCSNetK=20, Map Information=false2022.03———————0.280.540.110.190.290.60.210.440.150.340.210.42—————————————————————————
PECNetK=20, Error Unit=meters2020.06———————0.540.870.180.240.350.60.220.390.170.30.290.48—————————————————————————