About

Image Matting is the process of accurately estimating the foreground object in images and videos. It is a very important technique in image and video editing applications, particularly in film production for creating visual effects. In case of image segmentation, we segment the image into foreground and background by labeling the pixels. Image segmentation generates a binary image, in which a pixel either belongs to foreground or background. However, Image Matting is different from the image segmentation, wherein some pixels may belong to foreground as well as background, such pixels are called partial or mixed pixels. In order to fully separate the foreground from the background in an image, accurate estimation of the alpha values for partial or mixed pixels is necessary.

Source: Automatic Trimap Generation for Image Matting

Image Source: Real-Time High-Resolution Background Matting

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Subtasks

Datasets

Greatest papers with code

Background Matting: The World is Your Green Screen

CVPR 2020 senguptaumd/Background-Matting

To bridge the domain gap to real imagery with no labeling, we train another matting network guided by the first network and by a discriminator that judges the quality of composites.

IMAGE MATTING

Real-Time High-Resolution Background Matting

14 Dec 2020PeterL1n/BackgroundMattingV2

We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU.

IMAGE MATTING

Is a Green Screen Really Necessary for Real-Time Portrait Matting?

24 Nov 2020ZHKKKe/MODNet

For portrait matting without the green screen, existing works either require auxiliary inputs that are costly to obtain or use multiple models that are computationally expensive.

IMAGE MATTING VIDEO MATTING

Deep Image Matting

CVPR 2017 foamliu/Deep-Image-Matting

We evaluate our algorithm on the image matting benchmark, our testing set, and a wide variety of real images.

SEMANTIC IMAGE MATTING

Semantic Human Matting

5 Sep 2018lizhengwei1992/Semantic_Human_Matting

SHM is the first algorithm that learns to jointly fit both semantic information and high quality details with deep networks.

IMAGE MATTING

End-to-end Animal Image Matting

30 Oct 2020JizhiziLi/animal-matting

Specifically, we propose a novel Glance and Focus Matting network (GFM), which employs a shared encoder and two separate decoders to learn both tasks in a collaborative manner for end-to-end animal image matting.

IMAGE MATTING SEMANTIC SEGMENTATION

Index Network

11 Aug 2019poppinace/indexnet_matting

By viewing the indices as a function of the feature map, we introduce the concept of "learning to index", and present a novel index-guided encoder-decoder framework where indices are self-learned adaptively from data and are used to guide the downsampling and upsampling stages, without extra training supervision.

GRAYSCALE IMAGE DENOISING IMAGE DENOISING IMAGE MATTING MONOCULAR DEPTH ESTIMATION SCENE SEGMENTATION

Indices Matter: Learning to Index for Deep Image Matting

ICCV 2019 poppinace/indexnet_matting

We show that existing upsampling operators can be unified with the notion of the index function.

SEMANTIC IMAGE MATTING

$F$, $B$, Alpha Matting

17 Mar 2020MarcoForte/FBA-Matting

Cutting out an object and estimating its opacity mask, known as image matting, is a key task in many image editing applications.

IMAGE MATTING

Natural Image Matting via Guided Contextual Attention

13 Jan 2020Yaoyi-Li/GCA-Matting

Inspired by affinity-based method and the successes of contextual attention in inpainting, we develop a novel end-to-end approach for natural image matting with a guided contextual attention module, which is specifically designed for image matting.

SEMANTIC IMAGE MATTING