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V0.3.0-TaxiBJ-Weights
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@Lupin1998 Lupin1998 released this 18 Jun 23:50
taxibj-weights
f09ce01

We provide traffic benchmark results on the popular TaxiBJ dataset using $4\rightarrow 4$ frames prediction setting. Metrics (MSE, MAE, SSIM, pSNR) of the best models are reported in three trials. Parameters (M), FLOPs (G), and V100 inference FPS (s) are also reported for all methods. All methods are trained by Adam optimizer with Cosine Annealing scheduler (5 epochs warmup and min lr is 1e-6) and single GPU.

STL Benchmarks on TaxiBJ

Method Setting Params FLOPs FPS MSE MAE SSIM PSNR Download
ConvLSTM-S 50 epoch 14.98M 20.74G 815 0.3358 15.32 0.9836 39.45 model | log
E3D-LSTM* 50 epoch 50.99M 98.19G 60 0.3427 14.98 0.9842 39.64 model | log
PhyDNet 50 epoch 3.09M 5.60G 982 0.3622 15.53 0.9828 39.46 model | log
PredNet 50 epoch 12.5M 0.85G 5031 0.3516 15.91 0.9828 39.29 model | log
PredRNN 50 epoch 23.66M 42.40G 416 0.3194 15.31 0.9838 39.51 model | log
MIM 50 epoch 37.86M 64.10G 275 0.3110 14.96 0.9847 39.65 model | log
MAU 50 epoch 4.41M 6.02G 540 0.3268 15.26 0.9834 39.52 model | log
PredRNN++ 50 epoch 38.40M 62.95G 301 0.3348 15.37 0.9834 39.47 model | log
PredRNN.V2 50 epoch 23.67M 42.63G 378 0.3834 15.55 0.9826 39.49 model | log
DMVFN 50 epoch 3.54M 0.057G 6347 3.3954 45.52 0.8321 31.14 model | log
SimVP+IncepU 50 epoch 13.79M 3.61G 533 0.3282 15.45 0.9835 39.45 model | log
SimVP+gSTA-S 50 epoch 9.96M 2.62G 1217 0.3246 15.03 0.9844 39.71 model | log
TAU 50 epoch 9.55M 2.49G 1268 0.3108 14.93 0.9848 39.74 model | log

Benchmark of MetaFormers on SimVP (MetaVP)

MetaFormer Setting Params FLOPs FPS MSE MAE SSIM PSNR Download
SimVP+IncepU 50 epoch 13.79M 3.61G 533 0.3282 15.45 0.9835 39.45 model | log
SimVP+gSTA-S 50 epoch 9.96M 2.62G 1217 0.3246 15.03 0.9844 39.71 model | log
ViT 50 epoch 9.66M 2.80G 1301 0.3171 15.15 0.9841 39.64 model | log
Swin Transformer 50 epoch 9.66M 2.56G 1506 0.3128 15.07 0.9847 39.65 model | log
Uniformer 50 epoch 9.52M 2.71G 1333 0.3268 15.16 0.9844 39.64 model | log
MLP-Mixer 50 epoch 8.24M 2.18G 1974 0.3206 15.37 0.9841 39.49 model | log
ConvMixer 50 epoch 0.84M 0.23G 4793 0.3634 15.63 0.9831 39.41 model | log
Poolformer 50 epoch 7.75M 2.06G 1827 0.3273 15.39 0.9840 39.46 model | log
ConvNeXt 50 epoch 7.84M 2.08G 1918 0.3106 14.90 0.9845 39.76 model | log
VAN 50 epoch 9.48M 2.49G 1273 0.3125 14.96 0.9848 39.72 model | log
HorNet 50 epoch 9.68M 2.54G 1350 0.3186 15.01 0.9843 39.66 model | log
MogaNet 50 epoch 9.96M 2.61G 1005 0.3114 15.06 0.9847 39.70 model | log
TAU 50 epoch 9.55M 2.49G 1268 0.3108 14.93 0.9848 39.74 model | log
Assets 48
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