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In this paper, we propose a transformer-based image matting model called MatteFormer, which takes full advantage of trimap information in the transformer block.
A bayesian approach to digital matting
Yung-Yu Chuang, Brian Curless, David H Salesin, and Richard Szeliski · 2001
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Poisson matting
Jian Sun, Jiaya Jia, Chi-Keung Tang, and Heung-Yeung Shum · 2004
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A closed-form solution to natural image matting
Anat Levin, Dani Lischinski, and Yair Weiss · 2007
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Optimized color sampling for robust matting
Jue Wang and Michael F Cohen · 2007
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Spectral matting
Anat Levin, Alex Rav-Acha, and Dani Lischinski · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning based digital matting
Yuanjie Zheng and Chandra Kambhamettu · 2009
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Shared sampling for real-time alpha matting
Eduardo SL Gastal and Manuel M Oliveira · 2010
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Fast matting using large kernel matting laplacian matrices
Kaiming He, Jian Sun, and Xiaoou Tang · 2010
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A global sampling method for alpha matting
Kaiming He, Christoph Rhemann, Carsten Rother, Xiaoou Tang, and Jian Sun · 2011
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Nonlocal matting
Philip Lee and Ying Wu · 2011
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Knn matting
Qifeng Chen, Dingzeyu Li, and Chi-Keung Tang · 2013
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Improving image matting using comprehensive sampling sets
Ehsan Shahrian, Deepu Rajan, Brian Price, and Scott Cohen · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Deep image matting
Ning Xu, Brian Price, Scott Cohen, and Thomas Huang · 2017
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Alphagan: Generative adversarial networks for natural image matting
Sebastian Lutz, Konstantinos Amplianitis, and Aljosa Smolic · 2018
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Disentangled image matting
Shaofan Cai, Xiaoshuai Zhang, Haoqiang Fan, Haibin Huang, Jiangyu Liu, Jiaming Liu, Jiaying Liu, Jue Wang, and Jian Sun · 2019
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Context-aware image matting for simultaneous foreground and alpha estimation
Qiqi Hou and Feng Liu · 2019
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Indices matter: Learning to index for deep image matting
Hao Lu, Yutong Dai, Chunhua Shen, and Songcen Xu · 2019
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Learning-based sampling for natural image matting
Jingwei Tang, Yagiz Aksoy, Cengiz Oztireli, Markus Gross, and Tunc Ozan Aydin · 2019
Cited alongside, same era.
A late fusion cnn for digital matting
Yunke Zhang, Lixue Gong, Lubin Fan, Peiran Ren, Qixing Huang, Hujun Bao, and Weiwei Xu · 2019
Cited alongside, same era.
Toward transformer-based object detection
Josh Beal, Eric Kim, Eric Tzeng, Dong Huk Park, Andrew Zhai, and Dmitry Kislyuk · 2020
Towards enhancing fine-grained details for image matting
Chang Liu, Henghui Ding, and Xudong Jiang · 2021
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Transformer in convolutional neural networks
Yun Liu, Guolei Sun, Yu Qiu, Le Zhang, Ajad Chhatkuli, and Luc Van Gool · 2021
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Tripartite information mining and integration for image matting
Yuhao Liu, Jiake Xie, Xiao Shi, Yu Qiao, Yujie Huang, Yong Tang, and Xin Yang · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Efficient transformer for single image super-resolution
Zhisheng Lu, Hong Liu, Juncheng Li, and Linlin Zhang · 2021
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Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Natural image matting via guided contextual attention
Yaoyi Li and Hongtao Lu · 2020
Cited alongside, same era.
Attention-guided hierarchical structure aggregation for image matting
Yu Qiao, Yuhao Liu, Xin Yang, Dongsheng Zhou, Mingliang Xu, Qiang Zhang, and Xiaopeng Wei · 2020
Cited alongside, same era.
Background matting: The world is your green screen
Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steven M Seitz, and Ira Kemelmacher-Shlizerman · 2020
Cited alongside, same era.
Visual transformers: Token-based image representation and processing for computer vision
Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, and Peter Vajda · 2020
Cited alongside, same era.
Later among the works it cites.
Tokenlearner: What can 8 learned tokens do for images and videos?
Michael S Ryoo, AJ Piergiovanni, Anurag Arnab, Mostafa Dehghani, and Anelia Angelova · 2021
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Semantic image matting
Yanan Sun, Chi-Keung Tang, and Yu-Wing Tai · 2021
Later among the works it cites.
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Scaling local self-attention for parameter efficient visual backbones
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake Hechtman, and Jonathon Shlens · 2021
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High-fidelity pluralistic image completion with transformers
Ziyu Wan, Jingbo Zhang, Dongdong Chen, and Jing Liao · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Anchor detr: Query design for transformer-based detector
Yingming Wang, Xiangyu Zhang, Tong Yang, and Jian Sun · 2021
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Cvt: Introducing convolutions to vision transformers
Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang · 2021
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Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
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Focal self-attention for local-global interactions in vision transformers
Jianwei Yang, Chunyuan Li, Pengchuan Zhang, Xiyang Dai, Bin Xiao, Lu Yuan, and Jianfeng Gao · 2021
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Mask guided matting via progressive refinement network
Qihang Yu, Jianming Zhang, He Zhang, Yilin Wang, Zhe Lin, Ning Xu, Yutong Bai, and Alan Yuille · 2021
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Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zihang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
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Multi-scale vision longformer: A new vision transformer for high-resolution image encoding
Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, and Jianfeng Gao · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
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