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Video Prediction On Moving Mnist

Métriques

MAE
MSE
SSIM

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
MAE
MSE
SSIM
Paper TitleRepository
ConvLSTM182.9103.30.707Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
MSPred-34.440.975MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks
MAU-27.60.937MAU: A Motion-Aware Unit for Video Prediction and Beyond-
IAM4VPx549.215.30.966Implicit Stacked Autoregressive Model for Video Prediction
PredFormer41.9611.620.9742Video Prediction Transformers without Recurrence or Convolution
CrevNet+ST-LSTM-22.30.949Efficient and Information-Preserving Future Frame Prediction and Beyond-
VAN (SimVP 10x)53.5716.210.9646MogaNet: Multi-order Gated Aggregation Network
Swin (SimVP 10x)59.8419.11-MogaNet: Multi-order Gated Aggregation Network
ConvMixer (SimVP 10x)67.3722.3-MogaNet: Multi-order Gated Aggregation Network
CrevNet+ConvLSTM-38.50.928Efficient and Information-Preserving Future Frame Prediction and Beyond-
Uniformer (SimVP 10x)57.5218.01-MogaNet: Multi-order Gated Aggregation Network
E3D-LSTM86.441.30.910Eidetic 3D LSTM: A Model for Video Prediction and Beyond-
PredRNN-V2-48.40.891PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
MIM116.552.00.874Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics
TAU60.319.80.957Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning
SwinLSTM-17.70.962SwinLSTM: Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM-
MLP-Mixer (SimVP 10x)59.8618.85-MogaNet: Multi-order Gated Aggregation Network
SA-ConvLSTM94.743.90.913Self-Attention ConvLSTM for Spatiotemporal Prediction-
ViT (SimVP 10x)61.6519.740.9539MogaNet: Multi-order Gated Aggregation Network
MogaNet (SimVP 10x)51.8415.670.9661MogaNet: Multi-order Gated Aggregation Network
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