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https://github.com/kshitijagrwl/awesome-image-matting
A curated list of research and resources for image matting
https://github.com/kshitijagrwl/awesome-image-matting
List: awesome-image-matting
Last synced: 3 months ago
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A curated list of research and resources for image matting
- Host: GitHub
- URL: https://github.com/kshitijagrwl/awesome-image-matting
- Owner: kshitijagrwl
- License: mit
- Created: 2023-07-09T07:42:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-08-10T18:42:50.000Z (about 1 year ago)
- Last Synced: 2024-05-21T01:48:04.174Z (6 months ago)
- Size: 5.86 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# awesome-image-matting [](https://awesome.re)
This list contains updated set of research and resources for image matting.
Natural **image matting** is a fundamental and challenging computer vision task, which aims to predict an alpha matte from a given image. It has many applications in image editing and composition.
Over the last few years (2016-), deep learning based approaches have achieved great improvements in image matting. Image matting task while being similar to semantic segmentation, generates a more natural and delicate foreground than semantic segmentation.
:star: If you find this repo useful, please star it!
#### Sections
- [Image Matting](#Image-Matting)
- [Video Matting](#Video-Matting)
- [Datasets](#Datasets)
- [Websites](#Websites)
- [Toolkits](#Toolkits)
- [Resources](#Resources)
#### Updates - Coming Soon
- [] Video Matting methods
- [] Text Matting methods
## Image Matting
**2023**
- Ultrahigh Resolution Image/Video Matting With Spatio-Temporal Sparsity [CVPR][paper](https://openaccess.thecvf.com/content/CVPR2023/html/Sun_Ultrahigh_Resolution_ImageVideo_Matting_With_Spatio-Temporal_Sparsity_CVPR_2023_paper.html)
- Mask-Guided Matting in the Wild [CVPR] [paper](https://openaccess.thecvf.com/content/CVPR2023/html/Park_Mask-Guided_Matting_in_the_Wild_CVPR_2023_paper.html)
- ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers [arxiv] [paper](https://arxiv.org/abs/2305.15272) [](https://github.com/hustvl/ViTMatte)
- AEMatter: Rethinking Context Aggregation in Natural Image Matting [arxiv] [paper](https://arxiv.org/abs/2304.01171v1) [](https://github.com/qlyoo/aematter)
- Referring Image Matting [CVPR] [paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Referring_Image_Matting_CVPR_2023_paper.pdf) [](https://github.com/JizhiziLi/RIM)
**2022**
- Highly Accurate Dichotomous Image Segmentation [ECCV] [paper](https://arxiv.org/pdf/2203.03041.pdf) [](https://github.com/xuebinqin/DIS)
- Human Instance Matting via Mutual Guidance and Multi-Instance Refinement [CVPR] [paper](https://arxiv.org/pdf/2205.10767v1.pdf) [](https://github.com/nowsyn/InstMatt)
- Hierarchical and Progressive Image Matting [TOMM] [paper](https://dl.acm.org/doi/pdf/10.1145/3540201)
- Unified Interactive Image Matting [arXiv] [paper](https://arxiv.org/pdf/2205.08324.pdf)
- Situational Perception Guided Image Matting [arXiv] [paper](https://arxiv.org/pdf/2204.09276.pdf)
- PP-Matting: High-Accuracy Natural Image Matting [arXiv] [paper](https://arxiv.org/pdf/2204.09433.pdf) [](https://github.com/PaddlePaddle/PaddleSeg) :thumbsup: :thumbsup:
- Improving Deep Image Matting Via Local Smoothness Assumption [ICME] [paper](https://arxiv.org/pdf/2112.13809.pdf) [](https://github.com/kfeng123/LSA-Matting)
- Rethinking Portrait Matting with Privacy Preserving [arXiv] [paper](https://arxiv.org/pdf/2203.16828.pdf) [](https://github.com/vitae-transformer/vitae-transformer-matting)
- MatteFormer: Transformer-Based Image Matting via Prior-Tokens [CVPR] [paper](https://arxiv.org/pdf/2203.15662.pdf) [](https://github.com/webtoon/matteformer)
- Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation [CVPR] [paper](https://arxiv.org/pdf/2201.06889.pdf)
**2021**
- Bridging Composite and Real: Towards End-to-end Deep Image Matting [IJCV] [paper](https://arxiv.org/pdf/2010.16188.pdf) [](https://github.com/JizhiziLi/GFM) :thumbsup:
- Long-Range Feature Propagating for Natural Image Matting [ACMMM] [paper](https://arxiv.org/pdf/2109.12252.pdf) [](https://github.com/qlyoo/lfpnet)
- Highly Efficient Natural Image Matting [BMVC] [paper](https://arxiv.org/pdf/2110.12748.pdf)
- Deep Image Matting with Flexible Guidance Input [BMVC] [paper](https://arxiv.org/pdf/2110.10898.pdf) [](https://github.com/charch-630/fgi-matting)
- Privacy-Preserving Portrait Matting [ACMMM] [paper](https://arxiv.org/pdf/2104.14222.pdf) [](https://github.com/JizhiziLi/P3M)
- Virtual Multi-Modality Self-Supervised Foreground Matting for
Human-Object Interaction [ICCV] [paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Xu_Virtual_Multi-Modality_Self-Supervised_Foreground_Matting_for_Human-Object_Interaction_ICCV_2021_paper.pdf)
- Tripartite Information Mining and Integration for Image Matting [ICCV] [paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Liu_Tripartite_Information_Mining_and_Integration_for_Image_Matting_ICCV_2021_paper.pdf) [](https://github.com/kelisiya/TIMI-Net)
- Cascade Image Matting with Deformable Graph Refinement [ICCV] [paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Yu_Cascade_Image_Matting_With_Deformable_Graph_Refinement_ICCV_2021_paper.pdf)
- Deep Automatic Natural Image Matting [IJCAI] [paper](https://arxiv.org/pdf/2107.07235.pdf) [](https://github.com/JizhiziLi/AIM)
- Real-Time High-Resolution Background Matting [CVPR] [paper](https://arxiv.org/abs/2012.07810.pdf) [](https://github.com/PeterL1n/BackgroundMattingV2) :thumbsup: :thumbsup: :thumbsup:
- Semantic Image Matting [CVPR] [paper](https://arxiv.org/pdf/2104.08201v1.pdf) [](https://github.com/nowsyn/SIM)
- Mask Guided Matting via Progressive Refinement Network [CVPR] [paper](https://arxiv.org/pdf/2012.06722.pdf) [](https://github.com/yucornetto/MGMatting)
- Improved Image Matting via Real-time User Clicks and Uncertainty Estimation [CVPR] [paper](https://arxiv.org/pdf/2012.08323.pdf)
- Salient Image Matting [CVPR] [paper](https://arxiv.org/pdf/2103.12337.pdf)
- Learning Affinity-Aware Upsampling for Deep Image Matting [CVPR] [paper](https://arxiv.org/pdf/2011.14288.pdf) [](https://github.com/dongdong93/a2u_matting)
- High-Resolution Deep Image Matting [AAAI] [paper](https://arxiv.org/pdf/2009.06613.pdf)
- Towards Enhancing Fine-grained Details for Image Matting [WACV] [paper](https://openaccess.thecvf.com/content/WACV2021/papers/Liu_Towards_Enhancing_Fine-Grained_Details_for_Image_Matting_WACV_2021_paper.pdf)
- Multi-scale Information Assembly for Image Matting [arXiv] [paper](https://arxiv.org/abs/2101.02391)
- Semantic-guided Automatic Natural Image Matting with Trimap Generation Network and Light-weight Non-local Attention [arXiv] [paper](https://arxiv.org/pdf/2103.17020.pdf)
- Alpha Matte Generation from Single Input for Portrait Matting [arXiv] [paper](https://arxiv.org/pdf/2106.03210.pdf)
**2020**
- Background Matting: The World Is Your Green Screen [CVPR] [paper](https://arxiv.org/abs/2004.00626) [](https://github.com/senguptaumd/Background-Matting) :thumbsup: :thumbsup: :thumbsup:
- Attention-Guided Hierarchical Structure Aggregation for Image Matting [CVPR] [paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Qiao_Attention-Guided_Hierarchical_Structure_Aggregation_for_Image_Matting_CVPR_2020_paper.pdf) [](https://github.com/wukaoliu/CVPR2020-HAttMatting)
- Boosting Semantic Human Matting With Coarse Annotations [CVPR] [paper](https://arxiv.org/pdf/2004.04955.pdf)
- Natural Image Matting via Guided Contextual Attention. [AAAI] [paper](http://arxiv.org/abs/2001.04069) [](https://github.com/Yaoyi-Li/GCA-Matting)
- Towards Light-Weight Portrait Matting via Parameter Sharing [EuroGraphics] [paper](https://onlinelibrary.wiley.com/doi/epdf/10.1111/cgf.14179)
- Hierarchical Opacity Propagation for Image Matting [arXiv] [paper](https://arxiv.org/pdf/2004.03249.pdf) [](https://github.com/Yaoyi-Li/HOP-Matting)
- MODNet: Is a Green Screen Really Necessary for Real-Time Portrait Matting? [arXiv] [paper](https://arxiv.org/pdf/2011.11961.pdf) [](https://github.com/ZHKKKe/MODNet) :thumbsup: :thumbsup:
- End-to-end Animal Image Matting [arXiv] [paper](https://arxiv.org/pdf/2010.16188.pdf) [](https://github.com/JizhiziLi/animal-matting)
- F, B, Alpha Matting [arXiv] [paper](https://arxiv.org/pdf/2003.07711.pdf) [](https://github.com/MarcoForte/FBA_Matting)
- AlphaNet: An Attention Guided Deep Network for Automatic Image Matting [arXiv] [paper](https://arxiv.org/pdf/2003.03613.pdf)
**2019**
- Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation [ICCV] [paper](https://arxiv.org/pdf/1909.09725v2.pdf) [](https://github.com/hqqxyy/Context-Aware-Matting)
- Indices Matter: Learning to Index for Deep Image Matting. [ICCV] [paper](https://arxiv.org/abs/1908.00672) [](https://github.com/poppinace/indexnet_matting)
- Disentangled Image Matting [ICCV] [paper](https://arxiv.org/pdf/1909.04686.pdf)
- A Late Fusion CNN for Digital Matting [CVPR] [paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_A_Late_Fusion_CNN_for_Digital_Matting_CVPR_2019_paper.pdf) [](https://github.com/yunkezhang/FusionMatting)
- Learning-Based Sampling for Natural Image Matting [CVPR] [paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Tang_Learning-Based_Sampling_for_Natural_Image_Matting_CVPR_2019_paper.pdf)
- Learning Transparent Object Matting [IJCV] [paper](https://arxiv.org/pdf/1907.11544.pdf)
**2018**
- TOM-Net: Learning Transparent Object Matting from a Single Image [CVPR] [paper](https://guanyingc.github.io/TOM-Net/files/tom-net_cvpr18.pdf) [dataset](http://www.visionlab.cs.hku.hk/data/TOM-Net/) [](https://github.com/guanyingc/TOM-Net)
- AlphaGAN: Generative Adversarial Networks for Natural Image Matting [BMVC] [paper](https://arxiv.org/pdf/1807.10088.pdf) [](https://github.com/CDOTAD/AlphaGAN-Matting)
- Semantic Human Matting [MM] [paper](https://arxiv.org/pdf/1809.01354.pdf) [](https://github.com/lizhengwei1992/Semantic_Human_Matting)
- Deep Propagation Based Image Matting [IJCAI] [paper](https://www.ijcai.org/proceedings/2018/0139.pdf)
**2017**
- DIM: Deep Image Matting [CVPR] [paper](https://arxiv.org/pdf/1703.03872.pdf) [](https://github.com/foamliu/Deep-Image-Matting-PyTorch) :thumbsup:
- Designing Effective Inter-Pixel Information Flow for Natural Image Matting [CVPR] [paper](https://openaccess.thecvf.com/content_cvpr_2017/papers/Aksoy_Designing_Effective_Inter-Pixel_CVPR_2017_paper.pdf) [extended paper](https://arxiv.org/pdf/1707.05055.pdf)
- Fast Deep Matting for Portrait Animation on Mobile Phone [ACMMM] [paper](https://arxiv.org/pdf/1707.08289.pdf)
**2016**
- Natural Image Matting Using Deep CNN [ECCV] [paper](http://www.eccv2016.org/files/posters/P-1B-43.pdf)
- Deep Automatic Portrait Matting [ECCV] [paper](http://www.cse.cuhk.edu.hk/~leojia/projects/automatting/papers/deepmatting.pdf)
**2015**
- Image Matting With KL-Divergence Based Sparse Sampling [ICCV] [paper](https://openaccess.thecvf.com/content_iccv_2015/papers/Karacan_Image_Matting_With_ICCV_2015_paper.pdf)
**2014**
**2013**
- Image Matting with Local and Nonlocal Smooth Priors [CVPR] [paper](https://openaccess.thecvf.com/content_cvpr_2013/papers/Chen_Image_Matting_with_2013_CVPR_paper.pdf)
- Improving Image Matting Using Comprehensive Sampling Sets [CVPR] [paper](https://openaccess.thecvf.com/content_cvpr_2013/papers/Chen_Image_Matting_with_2013_CVPR_paper.pdf)
- A Learning-Based Approach to Reduce JPEG Artifacts in Image Matting [ICCV] [paper](https://openaccess.thecvf.com/content_iccv_2013/papers/Choi_A_Learning-Based_Approach_2013_ICCV_paper.pdf)
**2009**
- A Perceptually Motivated Online Benchmark for Image Matting [CVPR] [paper](https://publik.tuwien.ac.at/files/PubDat_180666.pdf)
**2006**
- A Closed Form Solution to Natural Image Matting [CVPR] [paper](https://people.csail.mit.edu/alevin/papers/Matting-Levin-Lischinski-Weiss-CVPR06.pdf) [](https://github.com/MarcoForte/closed-form-matting)
## Video Matting
**2023**
- Ultrahigh Resolution Image/Video Matting With Spatio-Temporal Sparsity [CVPR] [paper](https://openaccess.thecvf.com/content/CVPR2023/html/Sun_Ultrahigh_Resolution_ImageVideo_Matting_With_Spatio-Temporal_Sparsity_CVPR_2023_paper.html)
- Adaptive Human Matting for Dynamic Videos [CVPR2] [paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Lin_Adaptive_Human_Matting_for_Dynamic_Videos_CVPR_2023_paper.pdf)
- End-to-End Video Matting With Trimap Propagation [CVPR] [paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_End-to-End_Video_Matting_With_Trimap_Propagation_CVPR_2023_paper.pdf)
**2022**
- Robust High-Resolution Video Matting with Temporal Guidance [WACV] [paper](https://arxiv.org/pdf/2108.11515.pdf) [](https://github.com/PeterL1n/RobustVideoMatting) :thumbsup: :thumbsup: :thumbsup:
**2021**
- MODNet-V: Improving Portrait Video Matting via Background Restoration [arXiv] [paper](https://arxiv.org/pdf/2109.11818.pdf)
- Video Matting via Consistency-Regularized Graph Neural Networks [ICCV] [paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Wang_Video_Matting_via_Consistency-Regularized_Graph_Neural_Networks_ICCV_2021_paper.pdf) [](https://github.com/TiantianWang/VideoMatting-CRGNN)
- Deep Video Matting via Spatio-Temporal Alignment and Aggregation [CVPR] [paper](https://arxiv.org/pdf/2104.11208.pdf) [](https://github.com/nowsyn/DVM)
- Attention-guided Temporal Coherent Video Object Matting [ACMMM] [paper](https://arxiv.org/pdf/2105.11427.pdf) [](https://github.com/yunkezhang/TCVOM)
**2015**
- Video Matting via Sparse and Low-Rank Representation [ICCV](https://openaccess.thecvf.com/content_iccv_2015/papers/Zou_Video_Matting_via_ICCV_2015_paper.pdf)
## Text Matting
**2021**
- ATM: Attentional Text Matting [WACV] [paper](https://openaccess.thecvf.com/content/WACV2021/papers/Kang_ATM_Attentional_Text_Matting_WACV_2021_paper.pdf) [](https://github.com/TextMatting/TextMatting)
## Datasets
- [Composition-1K](https://arxiv.org/pdf/1703.03872.pdf)
- [Distinctions-646](http://openaccess.thecvf.com/content_CVPR_2020/papers/Qiao_Attention-Guided_Hierarchical_Structure_Aggregation_for_Image_Matting_CVPR_2020_paper.pdf)
- [VideoMatte240K](https://arxiv.org/abs/2012.07810.pdf)
- [PhotoMatte-85](https://arxiv.org/abs/2012.07810.pdf)
- [DVM](https://arxiv.org/pdf/2104.11208.pdf)
- [RealWorldPortrait-636](https://arxiv.org/pdf/2012.06722.pdf)
## Websites
- https://www.remove.bg/ :thumbsup: :thumbsup:
- https://www.cutout.pro/ :thumbsup: :thumbsup:
- https://www.pixmiller.com/
- https://www.unscreen.com/
- http://www.aisegment.cn/matting.html
- https://ai.baidu.com/tech/body/seg
- https://open.versa-ai.com/demo/human-segmentation
## Toolkits
- https://github.com/hustvl/Matte-Anything
- https://github.com/PaddlePaddle/PaddleSeg [](https://github.com/PaddlePaddle/PaddleSeg) :thumbsup: :thumbsup:
- https://github.com/pymatting/pymatting [](https://github.com/pymatting/pymatting)
- https://github.com/open-mmlab/mmediting [](https://github.com/open-mmlab/mmediting)
## Credits
Inspired by [awesome image matting](https://github.com/wchstrife/Awesome-Image-Matting), [awesome-image-matting](https://github.com/michaelowenliu/awesome-image-matting).