Image Matting
96 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
Benchmarks
These leaderboards are used to track progress in Image Matting
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Libraries
Use these libraries to find Image Matting models and implementationsDatasets
Composition-1K
AIM-500
Distinctions-646
P3M-10k
PPM-100
withoutbg100 dataset
Most implemented papers
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition
ZHKKKe/MODNet
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MODNet is easy to be trained in an end-to-end manner.
Deep Image Matting
PaddlePaddle/PaddleSeg
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CVPR 2017
We evaluate our algorithm on the image matting benchmark, our testing set, and a wide variety of real images.
Index Network
poppinace/indexnet_matting
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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.
Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
vinthony/ghost-free-shadow-removal
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With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images.
Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos
jiupinjia/SkyAR
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This paper proposes a vision-based method for video sky replacement and harmonization, which can automatically generate realistic and dramatic sky backgrounds in videos with controllable styles.
ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers
hustvl/ViTMatte
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Recently, plain vision Transformers (ViTs) have shown impressive performance on various computer vision tasks, thanks to their strong modeling capacity and large-scale pretraining.
Intra-frame Object Tracking by Deblatting
rozumden/deblatting_python
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We propose a novel approach called Tracking by Deblatting based on the observation that motion blur is directly related to the intra-frame trajectory of an object.
Real-time deep hair matting on mobile devices
jtiger958/hair-segmentation-pytorch
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Augmented reality is an emerging technology in many application domains.
Semantic Human Matting
lizhengwei1992/Semantic_Human_Matting
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SHM is the first algorithm that learns to jointly fit both semantic information and high quality details with deep networks.
Towards Real-Time Automatic Portrait Matting on Mobile Devices
We tackle the problem of automatic portrait matting on mobile devices.
