Video Prediction On Kth

المقاييس

Cond

FVD

LPIPS

PSNR

Params (M)

Pred

SSIM

Train

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Cond	FVD	LPIPS	PSNR	Params (M)	Pred	SSIM	Train	Paper Title	Repository
SVG-LP (from Grid-keypoints)	10	157.9	0.129	23.91	22.8	40	0.800	10	Stochastic Video Generation with a Learned Prior	-
SAVP-VAE	10	-	-	27.77	-	20	0.852	-	Stochastic Adversarial Video Prediction	-
Znet	10	-	-	27.58	-	20	0.817	-	Z-Order Recurrent Neural Networks for Video Prediction	-
MCnet + Residual	10	-	-	26.29	-	20	0.806	-	Decomposing Motion and Content for Natural Video Sequence Prediction	-
Conv-TT-LSTM	10	-	0.196	27.62	-	20	0.815	-	Convolutional Tensor-Train LSTM for Spatio-temporal Learning	-
DVG	-	-	-	-	-	-	-	-	Diverse Video Generation using a Gaussian Process Trigger	-
LMC	10	-	159.8	27.5	-	40	0.879	-	Video Prediction Recalling Long-term Motion Context via Memory Alignment Learning	-
SLAMP	10	228 ± 5	0.0795±0.0034	29.39±0.30	-	30	0.8646±0.0050	10	SLAMP: Stochastic Latent Appearance and Motion Prediction	-
SV2P time-invariant (from Grid-keypoints)	10	253.5	0.260	25.70	8.3	40	0.772	10	Stochastic Variational Video Prediction	-
PredRNN-V2	10	-	0.139	28.37	-	20	0.839	-	PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning	-
SRVP	10	222 ± 3	0.0736±0.0029	29.69±032	-	30	0.8697±0.0046	10	Stochastic Latent Residual Video Prediction	-
Struct-VRNN (from Grid-keypoints)	10	395.0	0.124	24.29	2.3	40	0.766	10	Unsupervised Learning of Object Structure and Dynamics from Videos	-
ConvLSTM	10	-	0.231	23.58	-	20	0.712	-	Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting	-
MSNET	10	-	-	27.08	-	20	0.876	-	Mutual Suppression Network for Video Prediction using Disentangled Features	-
SV2P time-invariant (from Grid-keypoints)	10	209.5	0.232	25.87	8.3	40	0.782	10	Stochastic Variational Video Prediction	-
SAVP-VAE (from Grid-keypoints)	10	145.7	0.116	26.00	7.3	40	0.806	10	Stochastic Adversarial Video Prediction	-
VarNet	10	-	-	28.48	-	20	0.843	-	VarNet: Exploring Variations for Unsupervised Video Prediction
DFN	10	-	-	27.26	-	20	0.794	-	Dynamic Filter Networks	-
MCnet	10	-	-	25.95	-	20	0.804	-	Decomposing Motion and Content for Natural Video Sequence Prediction	-
Grid-keypoints	10	144.2	0.092	27.11	2.0	40	0.837	10	Accurate Grid Keypoint Learning for Efficient Video Prediction	-

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