to baselines like DeepPrior and SimilarityGraph, where results are more clear and natural than that our results. Nevertheless, the DeepPrior needs much more inference time than other else and the SimilarityGraph highly constrains on specific tasks due to its copy and paste solution.

Ablation Study
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In this section, we experiment with different parameters, inclusive of mask ratio and receptive field to explore how these factors may affect our model. Note that we perform all the following experiments on ESC-50.

We perform two set of experiments. In the first one, we fix the length of the mask and alter the receptive field by configuring the network architecture. And in the second experiment, we fix the receptive field and see how different mask sizes actually impact the performance.

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    Masked
   Time (s)
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  : L1 loss and Perceptual error of different masked time(sec) and receptive field on ESC-50. The masked field and receptive field are based on time axis. Error is calculated on validation set. Success presents whether the model successfully inpainted the whole masked part or failed on certain field. Fail means no change on the magnitude of inpainting part lasting a period even the model inpainted most of 