{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T19:59:17Z","timestamp":1760385557953,"version":"3.37.3"},"reference-count":72,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,4,12]],"date-time":"2017-04-12T00:00:00Z","timestamp":1491955200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,4,12]],"date-time":"2017-04-12T00:00:00Z","timestamp":1491955200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["0910908","1029430"],"award-info":[{"award-number":["0910908","1029430"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2017,9]]},"DOI":"10.1007\/s11263-017-1011-0","type":"journal-article","created":{"date-parts":[[2017,4,12]],"date-time":"2017-04-12T10:20:15Z","timestamp":1491992415000},"page":"169-186","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Salient Object Subitizing"],"prefix":"10.1007","volume":"124","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9954-6294","authenticated-orcid":false,"given":"Jianming","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Shugao","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Mehrnoosh","family":"Sameki","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0711-4313","authenticated-orcid":false,"given":"Stan","family":"Sclaroff","sequence":"additional","affiliation":[]},{"given":"Margrit","family":"Betke","sequence":"additional","affiliation":[]},{"given":"Zhe","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Xiaohui","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Brian","family":"Price","sequence":"additional","affiliation":[]},{"given":"Radom\u00edr","family":"M\u011bch","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,4,12]]},"reference":[{"key":"1011_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 (CVPR).","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"1011_CR2","doi-asserted-by":"crossref","unstructured":"Anoraganingrum, D. (1999). Cell segmentation with median filter and mathematical morphology operation. In International conference on image analysis and processing.","DOI":"10.1109\/ICIAP.1999.797734"},{"key":"1011_CR3","doi-asserted-by":"crossref","unstructured":"Arteta, C., Lempitsky, V., Noble, J. A., & Zisserman, A. (2014). Interactive object counting. In European conference on computer vision (ECCV).","DOI":"10.1007\/978-3-319-10578-9_33"},{"issue":"3","key":"1011_CR4","first-page":"327\u201334","volume":"5","author":"J Atkinson","year":"1976","unstructured":"Atkinson, J., Campbell, F. W., & Francis, M. R. (1976). The magic number $$4\\pm 0$$: A new look at visual numerosity judgements. Perception, 5(3), 327\u201334.","journal-title":"Perception"},{"key":"1011_CR5","doi-asserted-by":"crossref","unstructured":"Berg, T. L., & Berg, A. C. (2009). Finding iconic images. In IEEE conference on computer vision and pattern recognition (CVPR) workshops.","DOI":"10.1109\/CVPRW.2009.5204174"},{"key":"1011_CR6","doi-asserted-by":"crossref","unstructured":"Borji, A., Sihite, D. N., & Itti, L. (2012). Salient object detection: A benchmark. In European conference on computer vision (ECCV).","DOI":"10.1007\/978-3-642-33709-3_30"},{"key":"1011_CR7","doi-asserted-by":"crossref","DOI":"10.4324\/9781315807393","volume-title":"The development of numerical competence: Animal and human models","author":"ST Boysen","year":"2014","unstructured":"Boysen, S. T., & Capaldi, E. J. (2014). The development of numerical competence: Animal and human models. Hove: Psychology Press."},{"key":"1011_CR8","doi-asserted-by":"crossref","unstructured":"Chan, A. B., & Vasconcelos, N. (2009). Bayesian poisson regression for crowd counting. In IEEE international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2009.5459191"},{"key":"1011_CR9","doi-asserted-by":"crossref","unstructured":"Chan, A. B., Liang, Z.-S. J., & Vasconcelos, N. (2008). Privacy preserving crowd monitoring: Counting people without people models or tracking. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2008.4587569"},{"key":"1011_CR10","doi-asserted-by":"crossref","unstructured":"Chatfield, K., Lempitsky, V., Vedaldi, A., & Zisserman, A. (2011). The devil is in the details: An evaluation of recent feature encoding methods. In British Machine Vision Conference (BMVC).","DOI":"10.5244\/C.25.76"},{"key":"1011_CR11","doi-asserted-by":"crossref","unstructured":"Cheng, M.-M, Zhang, G.-X., Mitra, N. J., Huang, X., & Hu, S.-M. (2011). Global contrast based salient region detection. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2011.5995344"},{"issue":"3","key":"1011_CR12","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1109\/TPAMI.2014.2345401","volume":"37","author":"M-M Cheng","year":"2015","unstructured":"Cheng, M.-M., Mitra, N. J., Huang, X., Torr, P. H. S., & Hu, S.-M. (2015). Global contrast based salient region detection. IEEE Transaction on Pattern Analysis and Machine Intelligence, 37(3), 569\u2013582.","journal-title":"IEEE Transaction on Pattern Analysis and Machine Intelligence"},{"issue":"8","key":"1011_CR13","doi-asserted-by":"publisher","first-page":"957","DOI":"10.1109\/LSP.2014.2321751","volume":"21","author":"J Choi","year":"2014","unstructured":"Choi, J., Jung, C., Lee, J., & Kim, C. (2014). Determining the existence of objects in an image and its application to image thumbnailing. Signal Processing Letters, 21(8), 957\u2013961.","journal-title":"Signal Processing Letters"},{"key":"1011_CR14","doi-asserted-by":"crossref","unstructured":"Chua, T.-S., Tang, J., Hong, R., Li, H., Luo, Z., & Zheng, Y. (2009). NUS-WIDE: A real-world web image database from National University of Singapore. In Proceedings of the ACM international conference on image and video retrieval.","DOI":"10.1145\/1646396.1646452"},{"key":"1011_CR15","doi-asserted-by":"crossref","first-page":"400","DOI":"10.5951\/TCM.5.7.0400","volume":"5","author":"DH Clements","year":"1999","unstructured":"Clements, D. H. (1999). Subitizing: What is it? Why teach it? Teaching Children Mathematics, 5, 400\u2013405.","journal-title":"Teaching Children Mathematics"},{"issue":"04","key":"1011_CR16","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1017\/S0140525X00053437","volume":"11","author":"H Davis","year":"1988","unstructured":"Davis, H., & P\u00e9russe, R. (1988). Numerical competence in animals: Definitional issues, current evidence, and a new research agenda. Behavioral and Brain Sciences, 11(04), 561\u2013579.","journal-title":"Behavioral and Brain Sciences"},{"key":"1011_CR17","volume-title":"The number sense: How the mind creates mathematics","author":"S Dehaene","year":"2011","unstructured":"Dehaene, S. (2011). The number sense: How the mind creates mathematics. Oxford: Oxford University Press."},{"key":"1011_CR18","unstructured":"Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman J. (2007). The PASCAL visual object classes challenge 2007 (VOC2007) results. http:\/\/www.pascal-network.org\/challenges\/VOC\/voc2007\/workshop\/index.html ."},{"issue":"9","key":"1011_CR19","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb, P. F., Girshick, R. B., McAllester, D., & Ramanan, D. (2010). Object detection with discriminatively trained part-based models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(9), 1627\u20131645.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1011_CR20","unstructured":"Feng, J., Wei, Y., Tao, L., Zhang, C., & Sun, J. (2011). Salient object detection by composition. In IEEE international conference on computer vision (ICCV)."},{"key":"1011_CR21","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich feature hierarchies for accurate object detection and semantic segmentation. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2014.81"},{"key":"1011_CR22","doi-asserted-by":"crossref","unstructured":"Gopalakrishnan, V., Hu, Y., Rajan, D. (2009). Random walks on graphs to model saliency in images. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2009.5206767"},{"issue":"1","key":"1011_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4161\/cib.18149","volume":"5","author":"HJ Gross","year":"2012","unstructured":"Gross, H. J. (2012). The magical number four: A biological, historical and mythological enigma. Communicative & Integrative Biology, 5(1), 1\u20132.","journal-title":"Communicative & Integrative Biology"},{"issue":"1","key":"1011_CR24","doi-asserted-by":"publisher","first-page":"e4263","DOI":"10.1371\/journal.pone.0004263","volume":"4","author":"HJ Gross","year":"2009","unstructured":"Gross, H. J., Pahl, M., Si, A., Zhu, H., Tautz, J., & Zhang, S. (2009). Number-based visual generalisation in the honeybee. PLoS ONE, 4(1), e4263.","journal-title":"PLoS ONE"},{"key":"1011_CR25","unstructured":"Gurari, D., & Grauman, K. (2016). Visual question: Predicting if a crowd will agree on the answer. ArXiv preprint arXiv:1608.08188 ."},{"key":"1011_CR26","doi-asserted-by":"crossref","unstructured":"Heo, J.-P., Lin, Z., & Yoon, S.-E. (2014). Distance encoded product quantization. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2014.274"},{"key":"1011_CR27","unstructured":"Jaderberg, M., Simonyan, K., Vedaldi, A., & Zisserman, A. (2014). Synthetic data and artificial neural networks for natural scene text recognition. In Workshop on deep learning, NIPS."},{"issue":"2","key":"1011_CR28","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1111\/bjdp.12032","volume":"32","author":"BRJ Jansen","year":"2014","unstructured":"Jansen, B. R. J., Hofman, A. D., Straatemeier, M., Bers, B. M. C. W., Raijmakers, M. E. J., & Maas, H. L. J. (2014). The role of pattern recognition in children\u2019s exact enumeration of small numbers. British Journal of Developmental Psychology, 32(2), 178\u2013194.","journal-title":"British Journal of Developmental Psychology"},{"key":"1011_CR29","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1038\/003281a0","volume":"3","author":"WS Jevons","year":"1871","unstructured":"Jevons, W. S. (1871). The power of numerical discrimination. Nature, 3, 281\u2013282.","journal-title":"Nature"},{"key":"1011_CR30","doi-asserted-by":"crossref","unstructured":"Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., et al. (2014). Caffe: Convolutional architecture for fast feature embedding. In ACM international conference on multimedia.","DOI":"10.1145\/2647868.2654889"},{"key":"1011_CR31","doi-asserted-by":"publisher","first-page":"498","DOI":"10.2307\/1418556","volume":"62","author":"EL Kaufman","year":"1949","unstructured":"Kaufman, E. L., Lord, M. W., Reese, T. W., & Volkmann, J. (1949). The discrimination of visual number. The American Journal of Psychology, 62, 498\u2013525.","journal-title":"The American Journal of Psychology"},{"key":"1011_CR32","doi-asserted-by":"crossref","unstructured":"Kazemzadeh, S., Ordonez, V., Matten, M., & Berg, T. L. (2014). Referitgame: Referring to objects in photographs of natural scenes. In Conference on empirical methods in natural language processing (EMNLP).","DOI":"10.3115\/v1\/D14-1086"},{"key":"1011_CR33","unstructured":"Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems (NIPS)."},{"key":"1011_CR34","unstructured":"Lee, Y. J., Ghosh, J., & Grauman, K. (2012). Discovering important people and objects for egocentric video summarization. In IEEE conference on computer vision and pattern recognition (CVPR)."},{"key":"1011_CR35","unstructured":"Lempitsky, V., & Zisserman, A. (2010). Learning to count objects in images. In Advances in neural information processing systems (NIPS)."},{"issue":"1","key":"1011_CR36","doi-asserted-by":"publisher","first-page":"14:1","DOI":"10.1145\/2906152","volume":"49","author":"X Li","year":"2016","unstructured":"Li, X., Uricchio, T., Ballan, L., Bertini, M., Snoek, C. G. M., & Bimbo, A. D. (2016). Socializing the semantic gap: A comparative survey on image tag assignment, refinement, and retrieval. ACM Computing Surveys, 49(1), 14:1\u201314:39.","journal-title":"ACM Computing Surveys"},{"key":"1011_CR37","doi-asserted-by":"crossref","unstructured":"Li, Y., Hou, X., Koch, C., Rehg, J., & Yuille, A. (2014). The secrets of salient object segmentation. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2014.43"},{"key":"1011_CR38","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., et al. (2014). Microsoft COCO: Common objects in context. In European conference on computer vision (ECCV).","DOI":"10.1007\/978-3-319-10602-1_48"},{"issue":"2","key":"1011_CR39","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1109\/TPAMI.2010.70","volume":"33","author":"T Liu","year":"2011","unstructured":"Liu, T., Yuan, Z., Sun, J., Wang, J., Zheng, N., Tang, X., et al. (2011). Learning to detect a salient object. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(2), 353\u2013367.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"1011_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1037\/0096-3445.111.1.1","volume":"111","author":"G Mandler","year":"1982","unstructured":"Mandler, G., & Shebo, B. J. (1982). Subitizing: An analysis of its component processes. Journal of Experimental Psychology: General, 111(1), 1.","journal-title":"Journal of Experimental Psychology: General"},{"key":"1011_CR41","doi-asserted-by":"crossref","unstructured":"Nath, S. K., Palaniappan, K., & Bunyak, F. (2006). Cell segmentation using coupled level sets and graph-vertex coloring. In Medical image computing and computer-assisted intervention (MICCAI).","DOI":"10.1007\/11866565_13"},{"key":"1011_CR42","doi-asserted-by":"publisher","first-page":"162","DOI":"10.3389\/fpsyg.2013.00162","volume":"4","author":"M Pahl","year":"2013","unstructured":"Pahl, M., Si, A., & Zhang, S. (2013). Numerical cognition in bees and other insects. Frontiers in psychology, 4, 162.","journal-title":"Frontiers in psychology"},{"key":"1011_CR43","doi-asserted-by":"crossref","unstructured":"Peng, Xi., Sun, B., Ali, K., & Saenko, K. (2015). Learning deep object detectors from 3d models. In IEEE international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2015.151"},{"key":"1011_CR44","unstructured":"Piazza, M., & Dehaene, S. (2004). From number neurons to mental arithmetic: The cognitive neuroscience of number sense. The Cognitive Neurosciences (3rd ed.), pp. 865\u2013877."},{"key":"1011_CR45","doi-asserted-by":"crossref","unstructured":"Pinheiro, P. O., Lin, T.-Y, Collobert, R., & Dollr, P. (2016). Learning to refine object segments. In European conference on computer vision (ECCV).","DOI":"10.1007\/978-3-319-46448-0_5"},{"issue":"1","key":"1011_CR46","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1109\/TPAMI.2016.2537320","volume":"39","author":"J Pont-Tuset","year":"2017","unstructured":"Pont-Tuset, J., Arbelaez, P., Barron, J. T., Marques, F., & Malik, J. (2017). Multiscale combinatorial grouping for image segmentation and object proposal generation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(1), 128\u2013140.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1011_CR47","doi-asserted-by":"crossref","unstructured":"Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014). CNN features off-the-shelf: An astounding baseline for recognition. In IEEE conference on computer vision and pattern recognition (CVPR), DeepVision Workshop.","DOI":"10.1109\/CVPRW.2014.131"},{"issue":"3","key":"1011_CR48","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Hao, S., Krause, J., Satheesh, S., Ma, S., et al. (2015). Imagenet large scale visual recognition challenge. International Journal of Computer Vision (IJCV), 115(3), 211\u2013252.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1011_CR49","doi-asserted-by":"crossref","unstructured":"Scharfenberger, C., Waslander, S. L., Zelek, J. S., & Clausi, D. A. (2013). Existence detection of objects in images for robot vision using saliency histogram features. In IEEE international conference on computer and robot vision (CRV).","DOI":"10.1109\/CRV.2013.25"},{"key":"1011_CR50","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., & LeCun, Y. (2014). Overfeat: Integrated recognition, localization and detection using convolutional networks. In International conference on learning representations (ICLR)."},{"key":"1011_CR51","unstructured":"Shen, X., & Wu, Y. (2012). A unified approach to salient object detection via low rank matrix recovery. In IEEE conference on computer vision and pattern recognition (CVPR)."},{"key":"1011_CR52","unstructured":"Shin, D., He, Shu, Lee, G. M, Whinston, A. B., Cetintas, S., & Lee, K.-C. (2016). Content complexity, similarity, and consistency in social media: A deep learning approach. https:\/\/ssrn.com\/abstract=2830377 ."},{"key":"1011_CR53","unstructured":"Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. In ICLR."},{"key":"1011_CR54","doi-asserted-by":"crossref","unstructured":"Siva, P., Russell, C., Xiang, T., & Agapito, L. (2013). Looking beyond the image: Unsupervised learning for object saliency and detection. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2013.416"},{"key":"1011_CR55","doi-asserted-by":"crossref","unstructured":"Stark, M., Goesele, M., Schiele, B. (2010). Back to the future: Learning shape models from 3D CAD data. In British Machine Vision Conference (BMVC).","DOI":"10.5244\/C.24.106"},{"issue":"2","key":"1011_CR56","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1038\/nn.2996","volume":"15","author":"I Stoianov","year":"2012","unstructured":"Stoianov, I., & Zorzi, M. (2012). Emergence of a visual number sense in hierarchical generative models. Nature Neuroscience, 15(2), 194\u2013196.","journal-title":"Nature Neuroscience"},{"key":"1011_CR57","doi-asserted-by":"crossref","unstructured":"Subburaman, V. B., Descamps, A., & Carincotte, C. (2012). Counting people in the crowd using a generic head detector. In IEEE international conference on advanced video and signal-based surveillance (AVSS).","DOI":"10.1109\/AVSS.2012.87"},{"key":"1011_CR58","doi-asserted-by":"crossref","unstructured":"Sun, B., & Saenko, K. (2014). From virtual to reality: Fast adaptation of virtual object detectors to real domains. In British Machine Vision Conference (BMVC).","DOI":"10.5244\/C.28.82"},{"key":"1011_CR59","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., et al. (2015). Going deeper with convolutions. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"1011_CR60","doi-asserted-by":"crossref","unstructured":"Torralba, A., Murphy, K. P., Freeman, W. T., & Rubin, M. A. (2003). Context-based vision system for place and object recognition. In IEEE international conference on computer vision (ICCV).","DOI":"10.1023\/A:1023052124951"},{"issue":"1","key":"1011_CR61","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1037\/0033-295X.101.1.80","volume":"101","author":"LM Trick","year":"1994","unstructured":"Trick, L. M., & Pylyshyn, Z. W. (1994). Why are small and large numbers enumerated differently? A limited-capacity preattentive stage in vision. Psychological Review, 101(1), 80.","journal-title":"Psychological Review"},{"key":"1011_CR62","unstructured":"Vedaldi, A., & Fulkerson, B. (2008). VLFeat: An open and portable library of computer vision algorithms. http:\/\/www.vlfeat.org\/ ."},{"issue":"6","key":"1011_CR63","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1093\/brain\/123.6.1263","volume":"123","author":"PO Vuilleumier","year":"2000","unstructured":"Vuilleumier, P. O., & Rafal, R. D. (2000). A systematic study of visual extinction between-and within-field deficits of attention in hemispatial neglect. Brain, 123(6), 1263\u20131279.","journal-title":"Brain"},{"key":"1011_CR64","doi-asserted-by":"crossref","unstructured":"Wang, P., Wang, J., Zeng, G., Feng, J., Zha, H., & Li, S. (2012). Salient object detection for searched web images via global saliency. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2012.6248054"},{"key":"1011_CR65","doi-asserted-by":"crossref","unstructured":"Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010). Sun database: Large-scale scene recognition from abbey to zoo. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2010.5539970"},{"key":"1011_CR66","doi-asserted-by":"crossref","unstructured":"Xiong, B., & Grauman, K. (2014). Detecting snap points in egocentric video with a web photo prior. In European conference on computer vision (ECCV). Springer.","DOI":"10.1007\/978-3-319-10602-1_19"},{"key":"1011_CR67","unstructured":"Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A. C., Salakhutdinov, R., et al. (2015). Show, attend and tell: Neural image caption generation with visual attention. In Internation conference on machine learning (ICML)."},{"key":"1011_CR68","doi-asserted-by":"crossref","unstructured":"Zhang, J., Ma, S., Sameki, M., Sclaroff, S., Betke, M., Lin, Z., et al. (2015a). Salient object subitizing. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2015.7299031"},{"key":"1011_CR69","doi-asserted-by":"crossref","unstructured":"Zhang, J., Sclaroff, S., Lin, Z., Shen, X., Price, B., & M\u0115ch, R. (2015b). Minimum barrier salient object detection at 80 fps. In IEEE international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2015.165"},{"key":"1011_CR70","doi-asserted-by":"crossref","unstructured":"Zhang, J., Sclaroff, S., Lin, Z., Shen, X., Price, B., & M\u0115ch, R. (2016). Unconstrained salient object detection via proposal subset optimization. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2016.618"},{"key":"1011_CR71","doi-asserted-by":"crossref","unstructured":"Zhao, R., Ouyang, W., Li, H., & Wang, X. (2015). Saliency detection by multi-context deep learning. In IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2015.7298731"},{"key":"1011_CR72","unstructured":"Zou, W. Y., & McClelland, J. L. (2013). Progressive development of the number sense in a deep neural network. In Annual conference of the Cognitive Science Society (CogSci)."}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-017-1011-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-017-1011-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-017-1011-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,27]],"date-time":"2022-07-27T12:21:26Z","timestamp":1658924486000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-017-1011-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,12]]},"references-count":72,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,9]]}},"alternative-id":["1011"],"URL":"https:\/\/doi.org\/10.1007\/s11263-017-1011-0","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"type":"print","value":"0920-5691"},{"type":"electronic","value":"1573-1405"}],"subject":[],"published":{"date-parts":[[2017,4,12]]},"assertion":[{"value":"10 July 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 April 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}