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Learning effective deep portrait matting models requires training data of both high quality and large quantity.
W. Beyer, “Traveling-matte photography and the blue-screen system: a tutorial paper,” Journal of the SMPTE , vol. 74, no. 3, pp. 217–239, 1965
1965
Earlier work this paper cites.
D. E. Knuth, The Art of Computer Programming, Volume 1: Fundamental Algorithms . Addison-Wesley, 1997
1997
Earlier work this paper cites.
J. Sun, J. Jia, C.-K. Tang, and H.-Y. Shum, “Poisson matting,” in ACM SIGGRAPH 2004 Papers , 2004, pp. 315–321
2004
Earlier work this paper cites.
A. Levin, D. Lischinski, and Y. Weiss, “A closed-form solution to natural image matting,” IEEE transactions on pattern analysis and machine intelligence , vol. 30, no. 2, pp. 228–242, 2007
2007
Earlier work this paper cites.
J. Wang and M. F. Cohen, “Optimized color sampling for robust matting,” in 2007 IEEE Conference on Computer Vision and Pattern Recognition . IEEE, 2007, pp. 1–8
2007
Earlier work this paper cites.
J. Wang, M. F. Cohen et al. , “Image and video matting: a survey,” Foundations and Trends® in Computer Graphics and Vision , vol. 3, no. 2, pp. 97–175, 2008
2008
Earlier work this paper cites.
Y. Zheng, C. Kambhamettu, J. Yu, T. Bauer, and K. Steiner, “Fuzzymatte: A computationally efficient scheme for interactive matting,” in 2008 IEEE Conference on Computer Vision and Pattern Recognition . IEEE, 2008, pp. 1–8
2008
Earlier work this paper cites.
C. Rhemann, C. Rother, J. Wang, M. Gelautz, P. Kohli, and P. Rott, “A perceptually motivated online benchmark for image matting,” in 2009 IEEE conference on computer vision and pattern recognition . IEEE, 2009, pp. 1826–1833
2009
Earlier work this paper cites.
T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms . MIT press, 2009
2009
Earlier work this paper cites.
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes (voc) challenge,” International journal of computer vision , vol. 88, pp. 303–338, 2010
2010
Earlier work this paper cites.
S. Wright, Digital Compositing for Film and Video . Taylor & Francis, 2010
2010
Earlier work this paper cites.
S. Li, X. Kang, J. Hu, and B. Yang, “Image matting for fusion of multi-focus images in dynamic scenes,” Information Fusion , vol. 14, no. 2, pp. 147–162, 2013
2013
Earlier work this paper cites.
E. S. Varnousfaderani and D. Rajan, “Weighted color and texture sample selection for image matting,” IEEE Transactions on Image Processing , vol. 22, no. 11, pp. 4260–4270, 2013
2013
Earlier work this paper cites.
Q. Chen, D. Li, and C.-K. Tang, “Knn matting,” IEEE transactions on pattern analysis and machine intelligence , vol. 35, no. 9, pp. 2175–2188, 2013
2013
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13 . Springer, 2014, pp. 740–755
2014
Earlier work this paper cites.
M. Erofeev, Y. Gitman, D. S. Vatolin, A. Fedorov, and J. Wang, “Perceptually motivated benchmark for video matting.” in BMVC , vol. 1, 2015, p. 2
2015
Earlier work this paper cites.
J. Johnson, E. S. Varnousfaderani, H. Cholakkal, and D. Rajan, “Sparse coding for alpha matting,” IEEE Transactions on Image Processing , vol. 25, no. 7, pp. 3032–3043, 2016
2016
Earlier work this paper cites.
X. Shen, X. Tao, H. Gao, C. Zhou, and J. Jia, “Deep automatic portrait matting,” in Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I 14 . Springer, 2016, pp. 92–107
2016
Earlier work this paper cites.
Y. Aksoy, T. Ozan Aydin, and M. Pollefeys, “Designing effective inter-pixel information flow for natural image matting,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 29–37
2017
Earlier work this paper cites.
L. Karacan, A. Erdem, and E. Erdem, “Alpha matting with kl-divergence-based sparse sampling,” IEEE Transactions on Image Processing , vol. 26, no. 9, pp. 4523–4536, 2017
2017
Cited alongside, same era.
X. Li, K. Liu, Y. Dong, and D. Tao, “Patch alignment manifold matting,” IEEE transactions on neural networks and learning systems , vol. 29, no. 7, pp. 3214–3226, 2017
2017
Cited alongside, same era.
Y. Lee and S. Yang, “Parallel block sequential closed-form matting with fan-shaped partitions,” IEEE Transactions on Image Processing , vol. 27, no. 2, pp. 594–605, 2017
2017
Cited alongside, same era.
N. Xu, B. Price, S. Cohen, and T. Huang, “Deep image matting,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 2970–2979
2017
Cited alongside, same era.
H. Ding, H. Zhang, C. Liu, and X. Jiang, “Deep interactive image matting with feature propagation,” IEEE Transactions on Image Processing , vol. 31, pp. 2421–2432, 2022
2022
Later among the works it cites.
J. Li, J. Zhang, S. J. Maybank, and D. Tao, “Bridging composite and real: towards end-to-end deep image matting,” International Journal of Computer Vision , vol. 130, no. 2, pp. 246–266, 2022
2022
Later among the works it cites.
Z. Ke, J. Sun, K. Li, Q. Yan, and R. W. Lau, “Modnet: Real-time trimap-free portrait matting via objective decomposition,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 36, no. 1, 2022, pp. 1140–1147
2022
Later among the works it cites.
S. Lin, L. Yang, I. Saleemi, and S. Sengupta, “Robust high-resolution video matting with temporal guidance,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , 2022, pp. 238–247
2022
Later among the works it cites.
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2017
Cited alongside, same era.
J. Boda and D. Pandya, “A survey on image matting techniques,” in 2018 International Conference on Communication and Signal Processing (ICCSP) . IEEE, 2018, pp. 0765–0770
2018
Cited alongside, same era.
D. Cho, Y.-W. Tai, and I. S. Kweon, “Deep convolutional neural network for natural image matting using initial alpha mattes,” IEEE Transactions on Image Processing , vol. 28, no. 3, pp. 1054–1067, 2018
2018
Cited alongside, same era.
Q. Chen, T. Ge, Y. Xu, Z. Zhang, X. Yang, and K. Gai, “Semantic human matting,” in Proceedings of the 26th ACM international conference on Multimedia , 2018, pp. 618–626
2018
Cited alongside, same era.
X. Li, J. Li, and H. Lu, “A survey on natural image matting with closed-form solutions,” IEEE Access , vol. 7, pp. 136 658–136 675, 2019
2019
Cited alongside, same era.
Y. Zhang, L. Gong, L. Fan, P. Ren, Q. Huang, H. Bao, and W. Xu, “A late fusion cnn for digital matting,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2019, pp. 7469–7478
2019
Cited alongside, same era.
Y. Qiao, Y. Liu, X. Yang, D. Zhou, M. Xu, Q. Zhang, and X. Wei, “Attention-guided hierarchical structure aggregation for image matting,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 13 676–13 685
2020
Cited alongside, same era.
S. Sengupta, V. Jayaram, B. Curless, S. M. Seitz, and I. Kemelmacher-Shlizerman, “Background matting: The world is your green screen,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 2291–2300
2020
Cited alongside, same era.
H. Cai, F. Xue, L. Xu, and L. Guo, “Transmatting: Enhancing transparent objects matting with transformers,” in European conference on computer vision . Springer, 2022, pp. 253–269
2022
Later among the works it cites.
2023
Later among the works it cites.
G. Lin, C. Gao, J.-B. Huang, C. Kim, Y. Wang, M. Zwicker, and A. Saraf, “Omnimatterf: Robust omnimatte with 3d background modeling,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 23 471–23 480
2023
Later among the works it cites.
S. Ma, J. Li, J. Zhang, H. Zhang, and D. Tao, “Rethinking portrait matting with privacy preserving,” International journal of computer vision , vol. 131, no. 8, pp. 2172–2197, 2023
2023
Later among the works it cites.
Y. Sun, C.-K. Tang, and Y.-W. Tai, “Ultrahigh resolution image/video matting with spatio-temporal sparsity,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 14 112–14 121
2023
Later among the works it cites.
Q. Liu, S. Zhang, Q. Meng, B. Zhong, P. Liu, and H. Yao, “End-to-end human instance matting,” IEEE Transactions on Circuits and Systems for Video Technology , 2023
2023
Later among the works it cites.
Y. Qiao, Y. Liu, Z. Wei, Y. Wang, Q. Cai, G. Zhang, and X. Yang, “Hierarchical and progressive image matting,” ACM Transactions on Multimedia Computing, Communications and Applications , vol. 19, no. 2, pp. 1–23, 2023
2023
Later among the works it cites.
W.-L. Huang and M.-S. Lee, “End-to-end video matting with trimap propagation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 14 337–14 347
2023
Later among the works it cites.
Z. Ye, W. Liu, H. Guo, Y. Liang, C. Hong, H. Lu, and Z. Cao, “Unifying automatic and interactive matting with pretrained vits,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 25 585–25 594
2024
Later among the works it cites.
R. D. Burgert, B. L. Price, J. Kuen, Y. Li, and M. S. Ryoo, “Magick: A large-scale captioned dataset from matting generated images using chroma keying,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 22 595–22 604
2024
Later among the works it cites.
2024
Later among the works it cites.
J. Yao, X. Wang, S. Yang, and B. Wang, “Vitmatte: Boosting image matting with pre-trained plain vision transformers,” Information Fusion , vol. 103, p. 102091, 2024
2024
Later among the works it cites.
2024
Later among the works it cites.
Z. Wang, Q. Miao, Y. Xi, and P. Zhao, “Eformer: Enhanced transformer towards semantic-contour features of foreground for portraits matting,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 3880–3889
2024
Later among the works it cites.
J. Li, V. Goel, M. Ohanyan, S. Navasardyan, Y. Wei, and H. Shi, “Vmformer: End-to-end video matting with transformer,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , 2024, pp. 6678–6687
2024
Later among the works it cites.