Real-Time High-Resolution Background Matting. model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps .

• Download model / weights

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

• Download datasets

We provide several scripts in this repo for you to experiment with our model. More detailed 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.

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

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

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

Configure data_path.pth to point to your dataset. The original paper uses train_base.pth to train only the base model till convergence then use train_refine.pth to train the entire network end-to-end. More details are specified in the paper.