{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:26:52Z","timestamp":1740122812661,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T00:00:00Z","timestamp":1552694400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1007\/s11042-019-7403-0","type":"journal-article","created":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T08:03:03Z","timestamp":1552723383000},"page":"21309-21324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Low-rank weighted co-saliency detection via efficient manifold ranking"],"prefix":"10.1007","volume":"78","author":[{"given":"Tengpeng","family":"Li","sequence":"first","affiliation":[]},{"given":"Huihui","family":"Song","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1613-3401","authenticated-orcid":false,"given":"Kaihua","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Qingshan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Lian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,3,16]]},"reference":[{"key":"7403_CR1","doi-asserted-by":"crossref","unstructured":"Achanta R, Hemami S, Estrada F, Susstrunk S (2009) Frequency-tuned salient region detection. In: IEEE conference on computer vision and pattern recognition, pp 1597\u20131604","DOI":"10.1109\/CVPR.2009.5206596"},{"issue":"11","key":"7403_CR2","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk S (2012) Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7403_CR3","doi-asserted-by":"crossref","unstructured":"Batra D, Kowdle A, Parikh D, Luo J, Luo TL (2010) icoseg: Interactive co-segmentation with intelligent scribble guidance. In: IEEE conference on computer vision and pattern recognition, pp 3169\u20133176. IEEE","DOI":"10.1109\/CVPR.2010.5540080"},{"key":"7403_CR4","doi-asserted-by":"crossref","unstructured":"Boykov Y, Kolmogorov V (2001) An experimental comparison of min-cut\/max-flow algorithms for energy minimization in vision. In: International workshop on energy minimization methods in computer vision and pattern recognition, pp 359\u2013374","DOI":"10.1007\/3-540-44745-8_24"},{"issue":"11","key":"7403_CR5","doi-asserted-by":"publisher","first-page":"1222","DOI":"10.1109\/34.969114","volume":"23","author":"Y Boykov","year":"2001","unstructured":"Boykov Y, Veksler O, Zabih R (2001) Fast approximate energy minimization via graph cuts. IEEE Trans Pattern Anal Mach Intell 23(11):1222\u20131239","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"9","key":"7403_CR6","first-page":"4175","volume":"23","author":"X Cao","year":"2014","unstructured":"Cao X, Tao Z, Zhang B, Fu H, Feng W (2014) Self-adaptively weighted co-saliency detection via rank constraint. IEEE Trans Image Process 23(9):4175\u20134186","journal-title":"IEEE Trans Image Process"},{"key":"7403_CR7","doi-asserted-by":"crossref","unstructured":"Cao X, Cheng Y, Tao Z, Fu H (2014) Co-saliency detection via base reconstruction. In: Proceedings of ACM international conference on multimedia, pp 997\u20131000. ACM","DOI":"10.1145\/2647868.2655007"},{"key":"7403_CR8","unstructured":"Cao X, Tao Z, Zhang B, Huazhu F, Li X (2013) Saliency map fusion based on rank-one constraint. In: IEEE international conference on multimedia and expo, pp 1\u20136"},{"issue":"4","key":"7403_CR9","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/s00371-013-0867-4","volume":"30","author":"M-M Cheng","year":"2014","unstructured":"Cheng M-M, Mitra NJ, Huang X, Hu S-M (2014) Salientshape: Group saliency in image collections. Vis Comput 30(4):443\u2013453","journal-title":"Vis Comput"},{"issue":"10","key":"7403_CR10","doi-asserted-by":"publisher","first-page":"3766","DOI":"10.1109\/TIP.2013.2260166","volume":"22","author":"H Fu","year":"2013","unstructured":"Fu H, Cao X, Tu Z (2013) Cluster-based co-saliency detection. IEEE Trans Image Process 22(10):3766","journal-title":"IEEE Trans Image Process"},{"key":"7403_CR11","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.image.2016.03.005","volume":"44","author":"C Ge","year":"2016","unstructured":"Ge C, Keren F, Liu F, Li B, Yang J (2016) Co-saliency detection via inter and intra saliency propagation. Signal Process Image Commun 44:69\u201383","journal-title":"Signal Process Image Commun"},{"key":"7403_CR12","doi-asserted-by":"crossref","unstructured":"Huang R, Feng W, Sun J (2015) Saliency and co-saliency detection by low-rank multiscale fusion. In: IEEE international conference on multimedia and expo, pp 1\u20136","DOI":"10.1109\/ICME.2015.7177414"},{"issue":"11","key":"7403_CR13","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"2002","unstructured":"Itti L, Koch C, Niebur E (2002) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254\u20131259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7403_CR14","doi-asserted-by":"crossref","unstructured":"Jia Y, Han M (2013) Category-independent object-level saliency detection. In: IEEE international conference on computer vision, pp 1761\u20131768. IEEE","DOI":"10.1109\/ICCV.2013.221"},{"key":"7403_CR15","unstructured":"Jian M, Qi Q, Dong J, Sun X, Sun Y, Lam K-M (2017) Saliency detection using quaternionic distance based weber local descriptor and level priors. Multi Tools Appl 77:1\u201318"},{"key":"7403_CR16","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.jvcir.2018.03.008","volume":"53","author":"M Jian","year":"2018","unstructured":"Jian M, Qi Q, Dong J, Yin Y, Lam K-M (2018) Integrating qdwd with pattern distinctness and local contrast for underwater saliency detection. J Vis Commun Image Represent 53:31\u201341","journal-title":"J Vis Commun Image Represent"},{"issue":"12","key":"7403_CR17","doi-asserted-by":"publisher","first-page":"3365","DOI":"10.1109\/TIP.2011.2156803","volume":"20","author":"H Li","year":"2011","unstructured":"Li H, Ngan KN (2011) A co-saliency model of image pairs. IEEE Trans Image Process 20(12):3365\u20133375","journal-title":"IEEE Trans Image Process"},{"issue":"8","key":"7403_CR18","doi-asserted-by":"publisher","first-page":"1896","DOI":"10.1109\/TMM.2013.2271476","volume":"15","author":"H Li","year":"2013","unstructured":"Li H, Meng F, Ngan KN (2013) Co-salient object detection from multiple images. IEEE Trans Multimed 15(8):1896\u20131909","journal-title":"IEEE Trans Multimed"},{"key":"7403_CR19","doi-asserted-by":"crossref","unstructured":"Li L, Liu Z, Zou W, Zhang X, Meur OL (2014) Co-saliency detection based on region-level fusion and pixel-level refinement. In: IEEE international conference on multimedia and expo, pp 1\u20136","DOI":"10.1109\/ICME.2014.6890183"},{"issue":"5","key":"7403_CR20","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1109\/LSP.2014.2364896","volume":"22","author":"Y Li","year":"2014","unstructured":"Li Y, Keren F, Liu Z, Yang J (2014) Efficient saliency-model-guided visual co-saliency detection. IEEE Signal Process Lett 22(5):588\u2013592","journal-title":"IEEE Signal Process Lett"},{"issue":"1","key":"7403_CR21","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/LSP.2013.2292873","volume":"21","author":"Z Liu","year":"2013","unstructured":"Liu Z, Zou W, Li L, Shen L, Meur OL (2013) Co-saliency detection based on hierarchical segmentation. IEEE Signal Process Lett 21(1):88\u201392","journal-title":"IEEE Signal Process Lett"},{"issue":"1","key":"7403_CR22","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Ohtsu","year":"2007","unstructured":"Ohtsu N (2007) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62\u201366","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"7403_CR23","unstructured":"Partridge M, Jabri M (2002) Robust principal component analysis. In: Proceedings of the IEEE signal processing society workshop on neural networks for signal processing, pp 289\u2013298"},{"key":"7403_CR24","unstructured":"Qin Y, Lu H, Xu Y, Wang H (2015) Saliency detection via cellular automata. In: IEEE conference on computer vision and pattern recognition, pp 110\u2013119. IEEE"},{"issue":"3","key":"7403_CR25","doi-asserted-by":"publisher","first-page":"3387","DOI":"10.1007\/s11042-017-5152-5","volume":"77","author":"L Wang","year":"2018","unstructured":"Wang L, Gao C, Jian J, Tang L, Liu J (2018) Semantic feature based multi-spectral saliency detection. Multimed Tools Appl 77(3):3387\u20133403","journal-title":"Multimed Tools Appl"},{"key":"7403_CR26","doi-asserted-by":"crossref","unstructured":"Wei L, Zhao S, El Farouk Bourahla O, Li X, Wu F (2017) Group-wise deep co-saliency detection. In: Proceedings of the 26th international joint conference on artificial intelligence, pp 3041\u20133047. AAAI Press","DOI":"10.24963\/ijcai.2017\/424"},{"issue":"5","key":"7403_CR27","doi-asserted-by":"publisher","first-page":"6209","DOI":"10.1007\/s11042-016-3310-9","volume":"76","author":"D Xiang","year":"2017","unstructured":"Xiang D, Wang Z (2017) Salient object detection via saliency bias and diffusion. Multimed Tools Appl 76(5):6209\u20136228","journal-title":"Multimed Tools Appl"},{"key":"7403_CR28","doi-asserted-by":"crossref","unstructured":"Xu B, Bu J, Chen C, Cai D, He X, Liu W, Luo J (2011) Efficient manifold ranking for image retrieval. In: Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval, p 525\u2013534. ACM","DOI":"10.1145\/2009916.2009988"},{"key":"7403_CR29","doi-asserted-by":"crossref","unstructured":"Yang C, Zhang L, Huchuan L, Ruan X, Yang MH (2013) Saliency detection via graph-based manifold ranking. In: IEEE conference on computer vision and pattern recognition, pp 3166\u20133173","DOI":"10.1109\/CVPR.2013.407"},{"issue":"4","key":"7403_CR30","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1145\/3158674","volume":"9","author":"D Zhang","year":"2018","unstructured":"Zhang D, Huazhu F, Han J, Borji A, Li X (2018) A review of co-saliency detection algorithms: fundamentals, applications, and challenges. ACM Trans Intell Syst Technol 9(4):38","journal-title":"ACM Trans Intell Syst Technol"},{"issue":"2","key":"7403_CR31","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s11263-016-0907-4","volume":"120","author":"D Zhang","year":"2016","unstructured":"Zhang D, Han J, Li C, Wang J, Li X (2016) Detection of co-salient objects by looking deep and wide. Int J Comput Vis 120(2):215\u2013232","journal-title":"Int J Comput Vis"},{"issue":"5","key":"7403_CR32","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1109\/TPAMI.2016.2567393","volume":"39","author":"D Zhang","year":"2017","unstructured":"Zhang D, Meng D, Han J (2017) Co-saliency detection via a self-paced multiple-instance learning framework. IEEE Trans Pattern Anal Mach Intell 39 (5):865\u2013878","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7403_CR33","doi-asserted-by":"crossref","unstructured":"Zhu W, Liang S, Wei Y, Sun J (2014) Saliency optimization from robust background detection. In: IEEE conference on computer vision and pattern recognition, pp 2814\u20132821","DOI":"10.1109\/CVPR.2014.360"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7403-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-019-7403-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7403-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,15]],"date-time":"2020-03-15T00:13:26Z","timestamp":1584231206000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-019-7403-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,16]]},"references-count":33,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["7403"],"URL":"https:\/\/doi.org\/10.1007\/s11042-019-7403-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2019,3,16]]},"assertion":[{"value":"8 May 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 February 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 March 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}