Image Matting

94 papers with code • 8 benchmarks • 8 datasets

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

Libraries

Use these libraries to find Image Matting models and implementations

Most implemented papers

Non-Causal Tracking by Deblatting

rozumden/tbd 15 Sep 2019

Tracking by Deblatting stands for solving an inverse problem of deblurring and image matting for tracking motion-blurred objects.

Sub-frame Appearance and 6D Pose Estimation of Fast Moving Objects

rozumden/deblatting_python CVPR 2020

We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose and object appearance changes with a time step that is a fraction of the video frame exposure time.

$F$, $B$, Alpha Matting

marcoforte/fba_matting 17 Mar 2020

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

Camouflaged Object Detection

DengPingFan/SINet CVPR 2020

We present a comprehensive study on a new task named camouflaged object detection (COD), which aims to identify objects that are "seamlessly" embedded in their surroundings.

Real-Time High-Resolution Background Matting

PeterL1n/BackgroundMattingV2 CVPR 2021

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.

SAPA: Similarity-Aware Point Affiliation for Feature Upsampling

poppinace/sapa 26 Sep 2022

We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points with semantic similarity.

On Point Affiliation in Feature Upsampling

tiny-smart/sapa 17 Jul 2023

We introduce the notion of point affiliation into feature upsampling.

Information-Flow Matting

yaksoy/AffinityBasedMattingToolbox CVPR 2017

Our resulting novel linear system formulation can be solved in closed-form and is robust against several fundamental challenges of natural matting such as holes and remote intricate structures.

Fast Deep Matting for Portrait Animation on Mobile Phone

huochaitiantang/pytorch-fast-matting-portrait 26 Jul 2017

Finally, an automatic portrait animation system based on fast deep matting is built on mobile devices, which does not need any interaction and can realize real-time matting with 15 fps.