{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T00:07:28Z","timestamp":1775261248649,"version":"3.50.1"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030033972","type":"print"},{"value":"9783030033989","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-03398-9_13","type":"book-chapter","created":{"date-parts":[[2018,11,1]],"date-time":"2018-11-01T09:12:41Z","timestamp":1541063561000},"page":"144-154","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Double-Line Multi-scale Fusion Pedestrian Saliency Detection"],"prefix":"10.1007","author":[{"given":"Jiaxuan","family":"Zhuo","sequence":"first","affiliation":[]},{"given":"Jianhuang","family":"Lai","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,11,2]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Wang, G.C., Lai, J.H., Xie, X.H.: P2SNeT: can an image match a video for person re-identification in an end-to-end way? IEEE TCSVT (2017)","DOI":"10.1109\/TCSVT.2017.2748698"},{"issue":"2","key":"13_CR2","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1109\/TPAMI.2017.2666805","volume":"40","author":"YC Chen","year":"2018","unstructured":"Chen, Y.C., Zhu, X.T., Zheng, W.S., Lai, J.H.: Person re-identification by camera correlation aware feature augmentation. IEEE Trans. Pattern Anal. Mach. Intell. 40(2), 392\u2013408 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"13_CR3","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.1109\/TIP.2016.2545929","volume":"25","author":"SZ Chen","year":"2016","unstructured":"Chen, S.Z., Guo, C.C., Lai, J.H.: Deep ranking for person re-identification via joint representation learning. IEEE Trans. Image Process. 25(5), 2353\u20132367 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1016\/j.neucom.2015.05.072","volume":"168","author":"SC Shi","year":"2015","unstructured":"Shi, S.C., Guo, C.C., Lai, J.H., Chen, S.Z., Hu, X.J.: Person re-identification with multi-level adaptive correspondence models. Neurocomputing 168, 550\u2013559 (2015)","journal-title":"Neurocomputing"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Guo, C.C., Chen, S.Z., Lai, J.H., Hu, X.J., Shi, S.C.: Multi-shot person re-identification with automatic ambiguity inference and removal. In: 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, 24\u201328 August 2014, pp. 3540\u20133545 (2014)","DOI":"10.1109\/ICPR.2014.609"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Zhuo, J.X., Chen, Z.Y., Lai, J.H., Wang, G.C.: Occluded person re-identification. arXiv preprint arXiv:1804.02792 (2018)","DOI":"10.1109\/ICME.2018.8486568"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Zheng, W.S., Li, X., Xiang, T., Liao, S.C., Lai, J.H., Gong, S.G.: Partial person re-identification. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4678\u20134686 (2015)","DOI":"10.1109\/ICCV.2015.531"},{"key":"13_CR8","unstructured":"Kr\u00e4henb\u00fchl, P., Koltun, V.: Efficient inference in fully connected CRFs with Gaussian edge potentials. In: Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a Meeting Held 12\u201314 December 2011, Granada, Spain, pp. 109\u2013117 (2011)"},{"key":"13_CR9","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR, vol. abs\/1409.1556 (2014)"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K.M., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, 21\u201326 July 2017, pp. 936\u2013944 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"13_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2014 MICCAI 2015, Part III","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015, Part III. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"2","key":"13_CR12","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1109\/TPAMI.2010.70","volume":"33","author":"T Liu","year":"2011","unstructured":"Liu, T., et al.: Learning to detect a salient object. IEEE Trans. Pattern Anal. Mach. Intell. 33(2), 353\u2013367 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Yan, Q., Xu, L., Shi, J.P., Jia, J.Y.: Hierarchical saliency detection. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, USA, 23\u201328 June 2013, pp. 1155\u20131162 (2013)","DOI":"10.1109\/CVPR.2013.153"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Li, Y., Hou, X.D., Koch, C., Rehg, J.M., Yuille, A.L.: The secrets of salient object segmentation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, 23\u201328 June 2014, pp. 280\u2013287 (2014)","DOI":"10.1109\/CVPR.2014.43"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Li, G.B., Yu, Y.Z.: Visual saliency based on multiscale deep features. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7\u201312 June 2015, pp. 5455\u20135463 (2015)","DOI":"10.1109\/CVPR.2015.7299184"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, L.H., Lu, H.C., Ruan, X., Yang, M.H.: Saliency detection via graph-based manifold ranking. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, USA, 23\u201328 June 2013, pp. 3166\u20133173 (2013)","DOI":"10.1109\/CVPR.2013.407"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Luo, Z.M., Mishra, A., Achkar, A., Eichel, J., Li, S.Z., Jodoin, P.M.: Non-local deep features for salient object detection. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21\u201326, 2017, pp. 6593\u20136601 (2017)","DOI":"10.1109\/CVPR.2017.698"},{"key":"13_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/978-3-642-33712-3_3","volume-title":"Computer Vision \u2013 ECCV 2012, Part III","author":"Y Wei","year":"2012","unstructured":"Wei, Y., Wen, F., Zhu, W., Sun, J.: Geodesic saliency using background priors. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol. 7574, pp. 29\u201342. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33712-3_3"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, W.J., Liang, S., Wei, Y.C., Sun, J.: Saliency optimization from robust background detection. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, 23\u201328 June 2014, pp. 2814\u20132821 (2014)","DOI":"10.1109\/CVPR.2014.360"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Liu, H., Tao, S.N., Li, Z.Y.: Saliency detection via global-object-seed-guided cellular automata. In: 2016 IEEE International Conference on Image Processing, ICIP 2016, Phoenix, AZ, USA, 25\u201328 September 2016, pp. 2772\u20132776 (2016)","DOI":"10.1109\/ICIP.2016.7532864"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Wang, L.J., Lu, H.C., Ruan, X., Yang, M.H.: Deep networks for saliency detection via local estimation and global search. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7\u201312 June 2015, pp. 3183\u20133192 (2015)","DOI":"10.1109\/CVPR.2015.7298938"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Zhao, R., Ouyang, W.L., Li, H.H., Wang, X.G.: Saliency detection by multi-context deep learning. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7\u201312 June 2015, pp. 1265\u20131274 (2015)","DOI":"10.1109\/CVPR.2015.7298731"},{"key":"13_CR23","doi-asserted-by":"crossref","unstructured":"Li, G.B., Yu, Y.Z.: Deep contrast learning for salient object detection. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, 27\u201330 June 2016, pp. 478\u2013487 (2016)","DOI":"10.1109\/CVPR.2016.58"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-03398-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T22:53:21Z","timestamp":1775256801000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-03398-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030033972","9783030033989"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-03398-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"2 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/prcv.qyhw.net.cn\/?lang=en&meeting_id=255","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}