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V0.3.0-KTH20-Weights
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@Lupin1998 Lupin1998 released this 18 Jun 23:28
kth20-weights
f09ce01

We provide long-term prediction benchmark results on KTH Action dataset using $10\rightarrow 20$ frames prediction setting. Metrics (MSE, MAE, SSIM, pSNR, LPIPS) of the best models are reported in three trials. Parameters (M), FLOPs (G), and V100 inference FPS (s) are also reported for all methods. The default training setup is trained 100 epochs by Adam optimizer with a batch size of 16 and Onecycle scheduler on single GPU or 4GPUs, and we report the used GPU setups for each method (also shown in the config).

  • For a fair comparison of different methods, we provide config files in configs/kth. Notice that 4xbs4 indicates 4GPUs DDP training with a batch size of 4 on each GPU.
  • We provide config files in configs/kth/simvp.

STL Benchmarks on KTH

Method GPUs Params FLOPs FPS MSE MAE SSIM PSNR LPIPS Download
ConvLSTM 1xbs16 14.9M 1368.0G 16 47.65 445.5 0.8977 26.99 0.26686 model | log
E3D-LSTM 2xbs8 53.5M 217.0G 17 136.40 892.7 0.8153 21.78 0.48358 model | log
PredNet 1xbs16 12.5M 3.4G 399 152.11 783.1 0.8094 22.45 0.32159 model | log
PhyDNet 1xbs16 3.1M 93.6G 58 91.12 765.6 0.8322 23.41 0.50155 model | log
MAU 1xbs16 20.1M 399.0G 8 51.02 471.2 0.8945 26.73 0.25442 model | log
MIM 1xbs16 39.8M 1099.0G 17 40.73 380.8 0.9025 27.78 0.18808 model | log
PredRNN 1xbs16 23.6M 2800.0G 7 41.07 380.6 0.9097 27.95 0.21892 model | log
PredRNN++ 1xbs16 38.3M 4162.0G 5 39.84 370.4 0.9124 28.13 0.19871 model | log
PredRNN.V2 1xbs16 23.6M 2815.0G 7 39.57 368.8 0.9099 28.01 0.21478 model | log
DMVFN 1xbs16 3.5M 0.88G 727 59.61 413.2 0.8976 26.65 0.12842 model | log
SimVP+IncepU 2xbs8 12.2M 62.8G 77 41.11 397.1 0.9065 27.46 0.26496 model | log
SimVP+gSTA 4xbs4 15.6M 76.8G 53 45.02 417.8 0.9049 27.04 0.25240 model | log
TAU 4xbs4 15.0M 73.8G 55 45.32 421.7 0.9086 27.10 0.22856 model | log

Benchmark of MetaFormers Based on SimVP (MetaVP)

MetaFormer GPUs Params FLOPs FPS MSE MAE SSIM PSNR LPIPS Download
IncepU (SimVPv1) 2xbs8 12.2M 62.8G 77 41.11 397.1 0.9065 27.46 0.26496 model | log
gSTA (SimVPv2) 2xbs8 15.6M 76.8G 53 45.02 417.8 0.9049 27.04 0.25240 model | log
ViT 2xbs8 12.7M 112.0G 28 56.57 459.3 0.8947 26.19 0.27494 model | log
Swin Transformer 2xbs8 15.3M 75.9G 65 45.72 405.7 0.9039 27.01 0.25178 model | log
Uniformer 2xbs8 11.8M 78.3G 43 44.71 404.6 0.9058 27.16 0.24174 model | log
MLP-Mixer 2xbs8 20.3M 66.6G 34 57.74 517.4 0.8886 25.72 0.28799 model | log
ConvMixer 2xbs8 1.5M 18.3G 175 47.31 446.1 0.8993 26.66 0.28149 model | log
Poolformer 2xbs8 12.4M 63.6G 67 45.44 400.9 0.9065 27.22 0.24763 model | log
ConvNeXt 2xbs8 12.5M 63.9G 72 45.48 428.3 0.9037 26.96 0.26253 model | log
VAN 2xbs8 14.9M 73.8G 55 45.05 409.1 0.9074 27.07 0.23116 model | log
HorNet 2xbs8 15.3M 75.3G 58 46.84 421.2 0.9005 26.80 0.26921 model | log
MogaNet 2xbs8 15.6M 76.7G 48 42.98 418.7 0.9065 27.16 0.25146 model | log
TAU 2xbs8 15.0M 73.8G 55 45.32 421.7 0.9086 27.10 0.22856 model | log
Assets 48
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