Perceptual loss for image reconstruction in video prediction
In order to further improve the accuracy of scene image reconstruction by video prediction network,the paper proposed a multi-scale discriminator feature perceptual loss function with auto-encoder(MDF-AE):the core is to use a set of discriminators for images of different scales to form a loss network and extract image features;the discriminators were trained in stages by a single image generative adversarial network(SinGAN),and the image auto-encoder was used as the generator,then the image reconstruction error was introduced into the generated image for providing more accurate perceptual constraints on the image reconstruction when the network predicts future frames.Experimental results showed that using MDF-AE to train a video prediction network could help improve the quality and visualization effect of scene images reconstructed by the network in terms of structure,texture and color.
video predictionperceptual lossimage auto-encodersingle image generative adversarial networkgenerative adversarial training
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