Real-Time High-Resolution Background Matting

Official repository for the paper Real-Time High-Resolution Background Matting. Our model produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU.

• Visit project site
• Watch project video

 

Overview

• Download
  • Model / Weights
  • Video / Image Examples
  • Datasets
• Demo
  • Scripts
  • Notebooks
• Usage / Documentation
• Training
• Project members

 

Download

Model / Weights

• Download model / weights

Video / Image Examples

• HD videos (by Sengupta et al.) (Our model is more robust on HD footage)
• 4K videos and images

Datasets

• VideoMatte240K (Coming soon)
• PhotoMatte85 (Coming soon)

 

Demo

Scripts

We provide several scripts in this repo for you to experiment with our model. More detail instructions are included in the files.

• inference_images.py: Perform matting on a directory of images.
• inference_video.py: Perform matting on a video.
• inference_webcam.py: An interactive matting demo using your webcam.

Notebooks

Additionally, you can try our notebooks in Google Colab for performing matting on images and videos.

• Image matting (Colab)
• Video matting (Colab)

 

Usage / Documentation

You can run our model using PyTorch, TorchScript, TensorFlow, and ONNX. For detail about using our model, please check out the Usage / Documentation page.

 

Training

Training code will be released upon acceptance of the paper.

 

Project members

• Shanchuan Lin*, University of Washington
• Andrey Ryabtsev*, University of Washington
• Soumyadip Sengupta, University of Washington
• Brian Curless, University of Washington
• Steve Seitz, University of Washington
• Ira Kemelmacher-Shlizerman, University of Washington

^{* Equal contribution.}