We present a novel, purely affinity-based natural image matting algorithm. Our method relies
on carefully defined pixel-to-pixel connections that enable effective use of information …

Natural image matting estimates the alpha values of unknown regions in the trimap.
Recently, deep learning based methods propagate the alpha values from the known regions …

In this paper, we present a new image matting algorithm that achieves state-of-the-art
performance on a benchmark dataset of images. This is achieved by solving two major …

In this paper we propose the Matting Anything Model (MAM) an efficient and versatile
framework for estimating the alpha matte of any instance in an image with flexible and …

Image matting is the problem of determining for each pixel in an image whether it is
foreground, background, or the mixing parameter," alpha", for those pixels that are a mixture …

The goal of natural image matting is the estimation of opacities of a user-defined foreground
object that is essential in creating realistic composite imagery. Natural matting is a …

Natural image matting separates the foreground from background in fractional occupancy
which can be caused by highly transparent objects, complex foreground (eg, net or tree) …

Image matting is a key technique for image and video editing and composition.
Conventionally, deep learning approaches take the whole input image and an associated …

Image matting aims at extracting foreground elements from an image by means of color and
opacity (alpha) estimation. While a lot of progress has been made in recent years on …

Over the last few years, deep learning based approaches have achieved outstanding
improvements in natural image matting. Many of these methods can generate visually …