Video super-resolution method based on time attention and cyclic feedback network
A super-resolution and feedback network technology, applied in the field of video processing, can solve the problems of different contributions of visual information to the super-resolution reconstruction effect, and the feedback mechanism has not been fully utilized, so as to improve the video super-resolution effect and the detail reconstruction effect. Effect
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[0064] Such as figure 1 As shown, a video super-resolution method based on temporal attention and loop feedback network, including the following steps:
[0065] S1: Build a super-resolution network model, including a temporal attention module and a loop feedback module;
[0066] S2: Obtain a public video super-resolution training data set from the network and preprocess the data set to obtain a low-resolution (LR) video sequence for training;
[0067] In this embodiment, the videos in the existing public high-resolution dataset Vimeo-90k dataset are selected as the training video data, and the video data are preprocessed.
[0068] S3: Determine the target frame that needs to be super-resolution, upsample it, and obtain the preliminary super-resolution result that the target frame lacks details;
[0069] In this embodiment, the training video data is 5 frames, and the middle frame is selected as the target frame to be super-resolution, and the bicubic interpolation and upsamp...
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