SOTAVerified

Image Matting

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

Papers

Showing 201225 of 225 papers

TitleStatusHype
Polarized Color Screen Matting0
PolarMatte: Fully Computational Ground-Truth-Quality Alpha Matte Extraction for Images and Video using Polarized Screen Matting0
Post-Training Quantization for Video Matting0
Prior-Induced Information Alignment for Image Matting0
Privileged Prior Information Distillation for Image Matting0
Rendering Portraitures from Monocular Camera and Beyond0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset0
Salient Image Matting0
Scalable Matting: A Sub-linear Approach0
SGM-Net: Semantic Guided Matting Net0
SHDM-NET: Heat Map Detail Guidance with Image Matting for Industrial Weld Semantic Segmentation Network0
Simultaneous Video Defogging and Stereo Reconstruction0
Situational Perception Guided Image Matting0
SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting0
Smart Scribbles for Image Mating0
SOLO: A Simple Framework for Instance Segmentation0
Sparse Coding for Alpha Matting0
Towards Enhancing Fine-grained Details for Image Matting0
Training-Free Neural Matte Extraction for Visual Effects0
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation0
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans0
Video Editing with Temporal, Spatial and Appearance Consistency0
Video Magnification in Presence of Large Motions0
Video Matting via Consistency-Regularized Graph Neural Networks0
Video Matting via Sparse and Low-Rank Representation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DIMMSE14Unverified
2IndexNet-MattingMSE13Unverified
3Context-Aware MattingMSE8.2Unverified
4SIMMSE5.8Unverified
5LSAMattingMSE5.4Unverified
6FBAMattingMSE5.3Unverified
7PP-MattingMSE5Unverified
8LFPNetMSE4.1Unverified
9MatteFormerMSE4Unverified
10TMFNetMSE3.6Unverified
#ModelMetricClaimedVerifiedStatus
1SHMCSAD61.5Unverified
2LFSAD36.12Unverified
3HATTSAD28.01Unverified
4SHMSAD17.81Unverified
5GFM(r)SAD10.89Unverified
6GFM(d)SAD10.26Unverified
7GFM(r2b)SAD10.24Unverified
8GFM(r')SAD9.66Unverified
9StyleMatteSAD9.6Unverified
#ModelMetricClaimedVerifiedStatus
1LFSAD42.95Unverified
2HATTSAD25.99Unverified
3SHMSAD21.56Unverified
4GFMSAD13.2Unverified
5P3M-Net (r)SAD8.73Unverified
6StyleMatteSAD6.97Unverified
7P3M-Net (v)SAD6.24Unverified
#ModelMetricClaimedVerifiedStatus
1LFSAD191.74Unverified
2SHMSAD170.44Unverified
3U2NETSAD83.46Unverified
4GFMSAD52.66Unverified
5AIM-NetSAD43.92Unverified
6DiffMatteSAD16.31Unverified
#ModelMetricClaimedVerifiedStatus
1CAMMSE4.5Unverified
2BMMSE1.33Unverified
3IMMSE1.16Unverified
4Adobe LS-GANMSE0.97Unverified
#ModelMetricClaimedVerifiedStatus
1PP-MattingSAD40.69Unverified
2DCAMSAD31.27Unverified
3ViTMatteSAD17.05Unverified
4DiffMatteSAD15.5Unverified
#ModelMetricClaimedVerifiedStatus
1MODNet+MAD0.81Unverified
#ModelMetricClaimedVerifiedStatus
1MODNet+ (Our)MAD0.97Unverified