Saliency based multiple object cosegmentation by ensemble MIML learning-Reference-Cited by-同舟云学术

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Saliency based multiple object cosegmentation by ensemble MIML learning

Published:2020-08-20 Issue:41-42 Volume:79 Page:31299-31328
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Li Bo,Sun Zhengxing^ORCID,Xu Junfeng,Wang Shuang,Yu Peiwen

Funder

National High Technology 863 Research and Development Program of China

Innovative Research Group Project of the National Natural Science Foundation of China

National 616 Natural Science Foundation of China

Innovation Fund of State Key Laboratory for Novel Software 620 Technology

China Postdoctoral Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-020-09458-5.pdf

Reference105 articles.

1. Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Süsstrunk S (2012) SLIC Superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282

2. Arbeláez P A, Pont-Tuset J, Barron J T, Marqués F, Malik J (2014) Multiscale combinatorial grouping. In: CVPR, pp 328–335

3. Batra D, Kowdle A, Parikh D, Luo J, Chen T (2010) icoseg: interactive co-segmentation with intelligent scribble guidance. In: The twenty-third IEEE conference on computer vision and pattern recognition, CVPR 2010, San Francisco, CA, USA, 13–18 June 2010, pp 3169–3176

4. Batra D, Kowdle A, Parikh D, Luo J, Chen T (2011) Interactively co-segmentating topically related images with intelligent scribble guidance. Int J Comput Vis 93(3):273–292

5. Borji A, Tanner J (2016) Reconciling saliency and object center-bias hypotheses in explaining free-viewing fixations. IEEE Trans Neural Netw Learning Syst 27(6):1214–1226

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