HyperAI

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
PredFormer41.9611.620.9742PredFormer: Transformers Are Effective Spatial-Temporal Predictive Learners
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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