U-2-Net

Why we included this project

U-2-Net isolates the most salient object in an image and returns a clean cutout, which makes it a dependable first stop for background removal and portrait matting. The repository accompanies the Pattern Recognition 2020 paper and ships pretrained weights plus the scripts used to train, test, and run the network, so you can move from a raw photo to a masked result without reimplementing anything. Teams building photo editors or automated product-image tooling have plugged these weights in directly, and because the model keeps full-resolution output without the heavy preprocessing other segmentation approaches require, integration stays fairly simple. It is research code aimed at a specific task rather than a broad pipeline, so expect to wire it into your own application instead of getting a one-click product.