{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T09:31:14Z","timestamp":1769765474125,"version":"3.49.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,7,29]],"date-time":"2021-07-29T00:00:00Z","timestamp":1627516800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,29]],"date-time":"2021-07-29T00:00:00Z","timestamp":1627516800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771223"],"award-info":[{"award-number":["61771223"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.1007\/s11760-021-01987-2","type":"journal-article","created":{"date-parts":[[2021,7,29]],"date-time":"2021-07-29T06:02:51Z","timestamp":1627538571000},"page":"273-281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["No-reference stereoscopic image quality assessment using 3D visual saliency maps fused with three-channel convolutional neural network"],"prefix":"10.1007","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3236-3143","authenticated-orcid":false,"given":"Chaofeng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lixia","family":"Yun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shoukun","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,7,29]]},"reference":[{"key":"1987_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.image.2016.02.001","volume":"43","author":"B Appina","year":"2016","unstructured":"Appina, B., Khan, S., Channappayya, S.S.: No-reference stereoscopic image quality assessment using natural scene statistics. Signal Process. Image Commun. 43, 1\u201314 (2016)","journal-title":"Signal Process. Image Commun."},{"issue":"8","key":"1987_CR2","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1016\/j.image.2012.08.004","volume":"28","author":"AK Moorthy","year":"2013","unstructured":"Moorthy, A.K., Su, C.C., Mittal, A., et al.: Subjective evaluation of stereoscopic image quality. Signal Process. Image Commun. 28(8), 870\u2013883 (2013)","journal-title":"Signal Process. Image Commun."},{"issue":"6","key":"1987_CR3","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.1109\/TNNLS.2015.2461603","volume":"27","author":"W Zhang","year":"2016","unstructured":"Zhang, W., Borji, A., Wang, Z., et al.: The application of visual saliency models in objective image quality assessment: a statistical evaluation. IEEE Trans. Neural Netw. Learn. Syst. 27(6), 1266\u20131278 (2016)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1987_CR4","doi-asserted-by":"crossref","unstructured":"H\u00e4kkinen, A.J., Kawai, T., Takatalo, J., et al.: What do people look at when they watch stereoscopic movies? In: Proceedings of SPIE\u2014The International Society for Optical Engineering, vol. 7524, pp. 75240E-75240E-10 (2010)","DOI":"10.1117\/12.838857"},{"issue":"1","key":"1987_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1167\/9.1.29","volume":"9","author":"L Jansen","year":"2009","unstructured":"Jansen, L., Onat, S., K\u00f6nig, P.: Influence of disparity on fixation and saccades in free viewing of natural scenes. J. Vis. 9(1), 1\u201319 (2009)","journal-title":"J. Vis."},{"key":"1987_CR6","doi-asserted-by":"crossref","unstructured":"Yang, J., An, P., Ma, J., Li, K., Shen, L.: No-reference stereo image quality assessment by learning gradient dictionary-based color visual characteristics. In: Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1\u20135 (2018)","DOI":"10.1109\/ISCAS.2018.8351261"},{"issue":"3","key":"1987_CR7","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1006\/cviu.2000.0840","volume":"78","author":"A Maki","year":"2000","unstructured":"Maki, A., Nordlund, P., Eklundh, J.-O.: Attentional scene segmentation: integrating depth and motion. Comput. Vis. Image Underst. 78(3), 351\u2013373 (2000)","journal-title":"Comput. Vis. Image Underst."},{"issue":"8","key":"1987_CR8","doi-asserted-by":"publisher","first-page":"2014","DOI":"10.1109\/TVCG.2016.2600594","volume":"23","author":"W Wang","year":"2017","unstructured":"Wang, W., Shen, J., Yu, Y., Ma, K.-L.: Stereoscopic thumbnail creation via efficient stereo saliency detection. IEEE Trans. Vis. Comput. Graphics 23(8), 2014\u20132027 (2017)","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"issue":"6","key":"1987_CR9","doi-asserted-by":"publisher","first-page":"2625","DOI":"10.1109\/TIP.2014.2305100","volume":"23","author":"Y Fang","year":"2014","unstructured":"Fang, Y., Wang, J., Narwaria, M., Le Callet, P., Lin, W.: Saliency detection for stereoscopic images. IEEE Trans. Image Process. 23(6), 2625\u20132636 (2014)","journal-title":"IEEE Trans. Image Process."},{"key":"1987_CR10","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Kr\u00e4henb\u00fchl, P., Pritch, Y., Hornung, A.: Saliency filters: contrast based filtering for salient region detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 733\u2013740 (2012).","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"1987_CR11","doi-asserted-by":"crossref","unstructured":"Li, N., Sun, B., Yu, J.: A weighted sparse coding framework for saliency detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5216\u20135223 (2015)","DOI":"10.1109\/CVPR.2015.7299158"},{"key":"1987_CR12","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/j.sigpro.2016.01.019","volume":"125","author":"Y Liu","year":"2016","unstructured":"Liu, Y., Yang, J.C., Meng, Q.G., et al.: Stereoscopic image quality assessment method based on binocular combination saliency model. Signal. Process. 125, 237\u2013248 (2016)","journal-title":"Signal. Process."},{"key":"1987_CR13","doi-asserted-by":"publisher","first-page":"46706","DOI":"10.1109\/ACCESS.2019.2909073","volume":"7","author":"YF Li","year":"2019","unstructured":"Li, Y.F., Yang, F., Wan, W.B., et al.: No-reference stereoscopic image quality assessment based on visual attention and perception. IEEE Access 7, 46706\u201346716 (2019)","journal-title":"IEEE Access"},{"key":"1987_CR14","doi-asserted-by":"publisher","DOI":"10.1155\/2008\/659024","volume":"2008","author":"A Benoit","year":"2009","unstructured":"Benoit, A., Le Callet, P., Campisi, P., et al.: Quality assessment of stereoscopic images. EURASIP J. Image Video Process. 2008, 659024 (2009). https:\/\/doi.org\/10.1155\/2008\/659024","journal-title":"EURASIP J. Image Video Process."},{"key":"1987_CR15","unstructured":"You, J., Xing, L., Perkis, A., et al.: Perceptual quality assessment for stereoscopic images based on 2D image quality metrics and disparity analysis. In: Proceedings of International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Arizona, U.S.A., pp. 1\u20136 (2010)"},{"issue":"9","key":"1987_CR16","doi-asserted-by":"publisher","first-page":"3379","DOI":"10.1109\/TIP.2013.2267393","volume":"22","author":"MJ Chen","year":"2013","unstructured":"Chen, M.J., Cormack, L.K., Bovik, A.C.: No-reference quality assessment of natural stereopairs. IEEE Trans. Image Process. 22(9), 3379\u20133391 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"1987_CR17","doi-asserted-by":"crossref","unstructured":"Akhter, R., Sazzad, Z.M.P., Horita, Y., et al.: No-reference stereoscopic image quality assessment. In: Proceedings of Stereoscopic Displays and Applications XXI. International Society for Optics and Photonics, 75240T-75240T-12 (2010)","DOI":"10.1117\/12.838775"},{"key":"1987_CR18","doi-asserted-by":"crossref","unstructured":"Zhou, W., Wu, J., Lei, J., et al.: Salient object detection in stereoscopic 3D images using a deep convolutional residual autoencoder. In: IEEE Transactions on Multimedia, pp. 1\u201312 (2020)","DOI":"10.1109\/TMM.2020.3025166"},{"issue":"10","key":"1987_CR19","doi-asserted-by":"publisher","first-page":"3191","DOI":"10.1016\/j.patcog.2015.04.012","volume":"48","author":"W Zhang","year":"2015","unstructured":"Zhang, W., Zhang, Y., Ma, L., et al.: Multimodal learning for facial expression recognition. Pattern Recogn. 48(10), 3191\u20133202 (2015)","journal-title":"Pattern Recogn."},{"key":"1987_CR20","unstructured":"Zhou, W., Yuan, J., Lei, J., et al.: TSNet: three-stream self-attention network for RGB-D indoor semantic segmentation. In: IEEE intelligent systems, pp. 1\u20135 (2020)."},{"key":"1987_CR21","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1109\/LSP.2013.2291240","volume":"21","author":"Y Xu","year":"2014","unstructured":"Xu, Y., Du, J., Dai, L.-R., et al.: An experimental study on speech enhancement based on deep neural networks. IEEE Signal Process. Lett. 21, 65\u201368 (2014)","journal-title":"IEEE Signal Process. Lett."},{"key":"1987_CR22","unstructured":"Zhou, W., Liu, W., Lei, J.., et al.: Deep Binocular Fixation Prediction using a Hierarchical Multimodal Fusion Network. In: IEEE Transactions on Cognitive and Developmental Systems"},{"key":"1987_CR23","doi-asserted-by":"crossref","unstructured":"Kang, L., Ye, P., Li, Y., et al.: Convolutional neural networks for no-reference image quality assessment. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1733\u20131740 (2014)","DOI":"10.1109\/CVPR.2014.224"},{"key":"1987_CR24","doi-asserted-by":"crossref","unstructured":"Bosse, S., Maniry, D., Wiegand, T., et al.: A deep neural network for image quality assessment. In: Proceedings of IEEE international conference on image processing, pp. 3773\u20133777 (2016)","DOI":"10.1109\/ICIP.2016.7533065"},{"issue":"C","key":"1987_CR25","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.patcog.2016.01.034","volume":"59","author":"W Zhang","year":"2016","unstructured":"Zhang, W., Qu, C., Ma, L., et al.: Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network. Pattern Recognit. 59(C), 176\u2013187 (2016)","journal-title":"Pattern Recognit."},{"key":"1987_CR26","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1109\/TCI.2020.2993640","volume":"6","author":"W Zhou","year":"2020","unstructured":"Zhou, W., Lei, J.S., Jiang, Q.P.: Blind binocular visual quality predictor using deep fusion network. IEEE Trans. Comput. Imaging. 6, 883\u2013893 (2020)","journal-title":"IEEE Trans. Comput. Imaging."},{"key":"1987_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, L., Gu, Z., Li. H.: SDSP: a novel saliency detection method by combining simple priors. In: Proceedings of IEEE International Conference on Image Processing, pp. 171\u2013175 (2014)","DOI":"10.1109\/ICIP.2013.6738036"},{"key":"1987_CR28","doi-asserted-by":"crossref","unstructured":"Achanta, R., Hemami, S., Estrada, F., et al.: Frequency-tuned salient region detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1597\u20131604 (2009)","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"1987_CR29","doi-asserted-by":"crossref","unstructured":"Judd, T., Ehinger, K., Durand, F., et al.: Learning to predict where humans look. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2106\u20132113 (2010)","DOI":"10.1109\/ICCV.2009.5459462"},{"key":"1987_CR30","unstructured":"Wu, Y., Shen, X.: A unified approach to salient object detection via low rank matrix recovery. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 853\u2013860 (2012)"},{"key":"1987_CR31","doi-asserted-by":"crossref","unstructured":"Sun, D., Roth, S., Black, M.J.: Secrets of optical flow estimation and their principles. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2432\u20132439 (2010)","DOI":"10.1109\/CVPR.2010.5539939"},{"key":"1987_CR32","unstructured":"Nair, V., Hinton. G.E.: Rectified linear units improve restricted boltzmann machines. In: Proceedings of the 27th International Conference on Machine Learning (ICML-10), pp. 807\u2013814 (2010)"},{"issue":"4","key":"1987_CR33","first-page":"212","volume":"3","author":"GE Hinton","year":"2012","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., et al.: Improving neural networks by preventing coadaptation of feature detectors. Computer Science 3(4), 212\u2013223 (2012)","journal-title":"Computer Science"},{"key":"1987_CR34","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization (2014). arXiv:1412.6980"},{"issue":"4","key":"1987_CR35","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"issue":"8","key":"1987_CR36","first-page":"1821","volume":"19","author":"F Shao","year":"2017","unstructured":"Shao, F., Tian, W., Lin, W., et al.: Learning sparse representation for no-reference quality assessment of multiply distorted stereoscopic images. IEEE Image Qual. Assess.: error Vis. Struct. Similarity Multimed. 19(8), 1821\u20131836 (2017)","journal-title":"IEEE Image Qual. Assess.: error Vis. Struct. Similarity Multimed."},{"issue":"10","key":"1987_CR37","doi-asserted-by":"publisher","first-page":"4923","DOI":"10.1109\/TIP.2017.2725584","volume":"26","author":"H Oh","year":"2017","unstructured":"Oh, H., Ahn, S., Kim, J., et al.: Blind deep S3D image quality evaluation via local to global feature aggregation. IEEE Trans. Image Process. 26(10), 4923\u20134936 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"1987_CR38","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.sigpro.2017.12.002","volume":"145","author":"X Wang","year":"2018","unstructured":"Wang, X., Ma, L., Kwong, S., et al.: Quaternion representation based visual saliency for stereoscopic image quality assessment. Signal Process. 145, 202\u2013213 (2018)","journal-title":"Signal Process."},{"key":"1987_CR39","doi-asserted-by":"publisher","first-page":"8058","DOI":"10.1109\/ACCESS.2018.2890304","volume":"7","author":"T-J Liu","year":"2019","unstructured":"Liu, T.-J., Lin, C.-T., Liu, H.-H., et al.: Blind stereoscopic image quality assessment based on hierarchical learning. IEEE Access 7, 8058\u20138069 (2019)","journal-title":"IEEE Access"},{"key":"1987_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2018.08.066","volume":"474","author":"J Yang","year":"2019","unstructured":"Yang, J., Zhao, Y., Zhu, Y., et al.: Blind assessment for stereo images considering binocular characteristics and deep perception map based on deep belief network. Inf. Sci. 474, 1\u201317 (2019)","journal-title":"Inf. Sci."},{"issue":"14","key":"1987_CR41","doi-asserted-by":"publisher","first-page":"3915","DOI":"10.1364\/AO.57.003915","volume":"57","author":"J Yang","year":"2018","unstructured":"Yang, J., Sim, K., Jiang, B., et al.: No-reference stereoscopic image quality assessment based on hue summation-difference mapping image and binocular joint mutual filtering. Appl. Opt. 57(14), 3915\u20133926 (2018)","journal-title":"Appl. Opt."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-01987-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-021-01987-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-01987-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T20:22:10Z","timestamp":1642018930000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-021-01987-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,29]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["1987"],"URL":"https:\/\/doi.org\/10.1007\/s11760-021-01987-2","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,29]]},"assertion":[{"value":"13 September 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 May 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 July 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}