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Cutting out an object and estimating its opacity mask, known as image matting, is a key task in many image editing applications.
Chuang, Y.Y., Curless, B., Salesin, D.H., Szeliski, R.: A bayesian approach to digital matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. vol. 2, pp. 264–271 (December 2001)
2001
Earlier work this paper cites.
Brinkman, R.: The Art and Science of Digital Compositing: Techniques for Visual Effects, Animation and Motion Graphics (The Morgan Kaufmann Series in Computer Graphics). Morgan Kaufmann (2008)
2008
Earlier work this paper cites.
Levin, A., Lischinski, D., Weiss, Y.: A closed-form solution to natural image matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30
2008
Earlier work this paper cites.
Deng, J., Dong, W., Socher, R., Li, L., Li, K., Li, F.: Imagenet: A large-scale hierarchical image database. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (June 2009)
2009
Earlier work this paper cites.
Gastal, E.S., Oliveira, M.M.: Shared sampling for real-time alpha matting. In: Computer Graphics Forum. vol. 29, pp. 575–584. Wiley Online Library (2010)
2010
Earlier work this paper cites.
Price, B.L., Morse, B.S., Cohen, S.: Simultaneous foreground, background, and alpha estimation for image matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (June 2010)
2010
Earlier work this paper cites.
He, K., Rhemann, C., Rother, C., Tang, X., Sun, J.: A global sampling method for alpha matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 2049–2056 (June 2011). https://doi.org/10.1109/CVPR.2011.5995495
2011
Earlier work this paper cites.
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results. http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html
2012
Earlier work this paper cites.
Chen, Q., Li, D., Tang, C.: KNN matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 35
2013
Earlier work this paper cites.
Shahrian, E., Rajan, D., Price, B., Cohen, S.: Improving image matting using comprehensive sampling sets. In: Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on. pp. 636–643 (June 2013). https://doi.org/10.1109/CVPR.2013.88
2013
Earlier work this paper cites.
Shahrian, E., Rajan, D., Price, B., Cohen, S.: Improving image matting using comprehensive sampling sets. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 636–643 (2013)
2013
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) Proceedings of the European Conference on Computer Vision. pp. 740–755 (2014)
2014
Earlier work this paper cites.
Erofeev, M., Gitman, Y., Vatolin, D., Fedorov, A., Wang, J.: Perceptually motivated benchmark for video matting. In: Proceedings of the British Machine Vision Conference. pp. 99–1 (2015)
2015
Earlier work this paper cites.
Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention - MICCAI. pp. 234–241 (2015). https://doi.org/10.1007/978-3-319-24574-4_28
2015
Earlier work this paper cites.
Cho, D., Tai, Y.W., Kweon, I.: Natural image matting using deep convolutional neural networks. In: Proceedings of the European Conference on Computer Vision (October 2016)
2016
Cited alongside, same era.
Aksoy, Y., Aydin, T.O., Pollefeys, M.: Designing effective inter-pixel information flow for natural image matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (July 2017)
2017
Cited alongside, same era.
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 1125–1134 (2017)
2017
Cited alongside, same era.
Karacan, L., Erdem, A., Erdem, E.: Alpha matting with kl-divergence-based sparse sampling. IEEE Transactions on Image Processing 26
2017
Cited alongside, same era.
Zhang, X., Ng, R., Chen, Q.: Single image reflection separation with perceptual losses. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4786–4794 (2018)
2018
Later among the works it cites.
Cai, S., Zhang, X., Fan, H., Huang, H., Liu, J., Liu, J., Liu, J., Wang, J., Sun, J.: Disentangled image matting. In: Proceedings of the International Conference on Computer Vision (October 2019)
2019
Later among the works it cites.
Hou, Q., Liu, F.: Context-aware image matting for simultaneous foreground and alpha estimation. In: Proceedings of the International Conference on Computer Vision (October 2019)
2019
Later among the works it cites.
huochaitiantang: Pytorch implementation of deep image matting. https://github.com/huochaitiantang/pytorch-deep-image-matting (2019)
2019
Later among the works it cites.
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Karacan, L., Erdem, A., Erdem, E.: Alpha matting with kl-divergence-based sparse sampling. IEEE Transactions on Image Processing 26
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Shelhamer, E., Long, J., Darrell, T.: Fully convolutional networks for semantic segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 39
2017
Cited alongside, same era.
Xu, N., Price, B., Cohen, S., Huang, T.: Deep image matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (July 2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Joker316701882: Deep-image-matting (Sep 2018), https://github.com/Joker316701882/Deep-Image-Matting
2018
Cited alongside, same era.
Le, H., Mai, L., Price, B.L., Cohen, S., Jin, H., Liu, F.: Interactive boundary prediction for object selection. In: Proceedings of the European Conference on Computer Vision (2018)
2018
Cited alongside, same era.
Lutz, S., Amplianitis, K., Smolic, A.: Alphagan: Generative adversarial networks for natural image matting. In: Proceedings of the British Machine Vision Conference (September 2018)
2018
Cited alongside, same era.
2019
Later among the works it cites.
Lu, H., Dai, Y., Shen, C., Xu, S.: Indices matter: Learning to index for deep image matting. In: Proceedings of the International Conference on Computer Vision (October 2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
Tang, H., Huang, Y., Jing, M., Fan, Y., Zeng, X.: Very deep residual network for image matting. In: Proceedings of the IEEE International Conference on Image Processing (September 2019)
2019
Later among the works it cites.
Tang, J., Aksoy, Y., Oztireli, C., Gross, M., Aydin, T.O.: Learning-based sampling for natural image matting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (June 2019)
2019
Later among the works it cites.
Wang, G., Li, W., Aertsen, M., Deprest, J., Ourselin, S., Vercauteren, T.: Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks. NEUROCOMPUTING 338
2019
Later among the works it cites.
Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Free-form image inpainting with gated convolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4471–4480 (2019)
2019
Later among the works it cites.
Foamliu: Deep-image-matting-pytorch (Jan 2020), https://github.com/foamliu/Deep-Image-Matting-PyTorch
2020
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