Improving Propagation and Transformer for Video Inpainting

ProPainter is an open-source video inpainting model developed by researchers at Google AI. It is based on three components:

  1. Recurrent flow completion: This component uses a recurrent neural network to learn the temporal dependencies in a video and generate a flow field that can be used to complete masked areas.
  2. Dual-domain propagation: This component propagates information from both the spatial and temporal domains to refine the flow field and improve the quality of the inpainted video.
  3. Mask-guided sparse Transformer: This component uses a sparse Transformer to learn the global dependencies in a video and further improve the quality of the inpainted video.

ProPainter can be used to remove objects and watermarks, complete masked areas in videos, and extend any video view. It outperforms previous state-of-the-art video inpainting models on a variety of benchmarks.

Here is a summary of the key features of ProPainter:

  • Open-source and freely available
  • State-of-the-art performance on video inpainting benchmarks
  • Can be used to remove objects and watermarks, complete masked areas, and extend video views
  • Easy to use with a simple command-line interface

ProPainter is a powerful tool for video editing and restoration. It can be used to create professional-looking videos without the need for expensive software or skilled editors.

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