{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T12:46:59Z","timestamp":1778676419446,"version":"3.51.4"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T00:00:00Z","timestamp":1610064000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T00:00:00Z","timestamp":1610064000000},"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":["61527804"],"award-info":[{"award-number":["61527804"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s10489-020-01857-3","type":"journal-article","created":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T12:02:47Z","timestamp":1610107367000},"page":"5344-5357","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Saliency prediction on omnidirectional images with attention-aware feature fusion network"],"prefix":"10.1007","volume":"51","author":[{"given":"Dandan","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongqing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Defang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiangqiang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0564-5575","authenticated-orcid":false,"given":"Xiaokang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,8]]},"reference":[{"key":"1857_CR1","unstructured":"Reina MA, Nieto XG, McGuinness K, O\u2019Connor NE (2017) Saltinet: scan-path prediction on 360 degree images using saliency volumes. In: Proceedings of the IEEE international conference on computer vision, pp 2331\u20132338"},{"key":"1857_CR2","first-page":"53","volume":"69","author":"F Battisti","year":"2018","unstructured":"Battisti F, Baldoni S, Brizzi M, Carli M (2018) A feature-based approach for saliency estimation of omni-directional images. Signal Process: Image Commun 69:53\u201359","journal-title":"Signal Process: Image Commun"},{"key":"1857_CR3","doi-asserted-by":"crossref","unstructured":"Borji A (2012) Boosting bottom-up and top-down visual features for saliency estimation. In: 2012 Boosting IEEE conference on computer vision and pattern recognition, pp 438\u2013445","DOI":"10.1109\/CVPR.2012.6247706"},{"key":"1857_CR4","doi-asserted-by":"crossref","unstructured":"Corbillon X, De Simone F, Simon G (2017) 360-degree video head movement dataset. In: Proceedings of the 8th ACM on multimedia systems conference. ACM, pp 199\u2013204","DOI":"10.1145\/3083187.3083215"},{"key":"1857_CR5","doi-asserted-by":"crossref","unstructured":"Cornia M, Baraldi L, Serra G, Cucchiara R (2016) A deep multi-level network for saliency prediction. In: 2016 23rd International conference on pattern recognition (ICPR). IEEE, pp 3488\u20133493","DOI":"10.1109\/ICPR.2016.7900174"},{"issue":"10","key":"1857_CR6","doi-asserted-by":"publisher","first-page":"5142","DOI":"10.1109\/TIP.2018.2851672","volume":"27","author":"M Cornia","year":"2018","unstructured":"Cornia M, Baraldi L, Serra G, Cucchiara R (2018) Predicting human eye fixations via an lstm-based saliency attentive model. IEEE Trans Image Process 27(10):5142\u20135154","journal-title":"IEEE Trans Image Process"},{"key":"1857_CR7","doi-asserted-by":"crossref","unstructured":"David EJ, Gutierrez J, Coutrot A, Da Silva MP, Le Callet P (2018) A dataset of head and eye movements for 360 videos. In: Proceedings of the 9th ACM multimedia systems conference. ACM, pp 432\u2013437","DOI":"10.1145\/3204949.3208139"},{"key":"1857_CR8","doi-asserted-by":"crossref","unstructured":"De Abreu A, Ozcinar C, Smolic A (2017) Look around you: saliency maps for omnidirectional images in vr applications. In: 2017 Ninth international conference on quality of multimedia experience (QoMEX). IEEE, pp 1\u20136","DOI":"10.1109\/QoMEX.2017.7965634"},{"key":"1857_CR9","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li L-J, Li K, Fei-Fei L (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"1857_CR10","unstructured":"Harel J, Koch C, Perona P (2007) Graphbased visual saliency. In: Advances in neural information processing systems, pp 545\u2013552"},{"key":"1857_CR11","doi-asserted-by":"crossref","unstructured":"Hu B, Johnson-Bey I, Sharma M, Niebur E (2017) Head movements during visual exploration of natural images in virtual reality. In: 2017 51st Annual conference on information sciences and systems (CISS). IEEE, pp 1\u20136","DOI":"10.1109\/CISS.2017.7926138"},{"key":"1857_CR12","doi-asserted-by":"crossref","unstructured":"Hu H-N, Lin Y-C, Liu M-Y, Cheng H-T, Chang Y-J, Sun M (2017) Deep 360 pilot: learning a deep agent for piloting through 360 sports videos. In: 2017 IEEE conference on computer vision and pattern recognition (CVPR). IEEE, pp 1396\u20131405","DOI":"10.1109\/CVPR.2017.153"},{"key":"1857_CR13","doi-asserted-by":"crossref","unstructured":"Huang X, Shen C, Boix X, Zhao Q (2015) Salicon: reducing the semantic gap in saliency prediction by adapting deep neural networks. In: Proceedings of the IEEE international conference on computer vision, pp 262\u2013270","DOI":"10.1109\/ICCV.2015.38"},{"issue":"11","key":"1857_CR14","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti L, Koch C, Niebur E (1998) 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":"1857_CR15","unstructured":"Judd T, Durand F, Torralba A (2012) A benchmark of computational models of saliency to predict human fixations., MIT tech report, Tech. Rep"},{"key":"1857_CR16","doi-asserted-by":"crossref","unstructured":"Judd T, Ehinger K, Durand F, Torralba A (2009) Learning to predict where humans look. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 2106\u20132113","DOI":"10.1109\/ICCV.2009.5459462"},{"issue":"9","key":"1857_CR17","doi-asserted-by":"publisher","first-page":"4446","DOI":"10.1109\/TIP.2017.2710620","volume":"26","author":"SSS Kruthiventi","year":"2017","unstructured":"Kruthiventi SSS, Ayush K, Babu RV (2017) Deepfix: a fully convolutional neural network for predicting human eye fixations. IEEE Trans Image Process 26(9):4446\u20134456","journal-title":"IEEE Trans Image Process"},{"issue":"19","key":"1857_CR18","doi-asserted-by":"publisher","first-page":"2483","DOI":"10.1016\/j.visres.2007.06.015","volume":"47","author":"O Le Meur","year":"2007","unstructured":"Le Meur O, Le Callet P, Barba D (2007) Predicting visual fixations on video based on low-level visual features. Vis Res 47(19):2483\u20132498","journal-title":"Vis Res"},{"key":"1857_CR19","first-page":"69","volume":"69","author":"P Lebreton","year":"2018","unstructured":"Lebreton P, Raake A (2018) Gbvs360, bms360, prosal: extending existing saliency prediction models from 2d to omnidirectional images. Signal Process: Image Commun 69:69\u201378","journal-title":"Signal Process: Image Commun"},{"key":"1857_CR20","doi-asserted-by":"crossref","unstructured":"Lo W-C, Fan C-L, Lee J, Huang C-Y, Chen K-T, Hsu C-H (2017) 360 video viewing dataset in head-mounted virtual reality. In: Proceedings of the 8th ACM on multimedia systems conference. ACM, pp 211\u2013216","DOI":"10.1145\/3083187.3083219"},{"key":"1857_CR21","first-page":"26","volume":"69","author":"R Monroy","year":"2018","unstructured":"Monroy R, Lutz S, Chalasani T, Smolic A (2018) Salnet360: saliency maps for omni-directional images with cnn. Signal Process: Image Commun 69:26\u201334","journal-title":"Signal Process: Image Commun"},{"key":"1857_CR22","doi-asserted-by":"crossref","unstructured":"Otani M, Nakashima Y, Rahtu E, Heikkila J, Yokoya N (2016) Video summarization using deep semantic features. In: Asian conference on computer vision. Springer, pp 361\u2013 377","DOI":"10.1007\/978-3-319-54193-8_23"},{"key":"1857_CR23","doi-asserted-by":"crossref","unstructured":"Ozcinar C, Smolic A (2018) Visual attention in omnidirectional video for virtual reality applications. In: 2018 Tenth international conference on quality of multimedia experience (QoMEX), pp 1\u20136","DOI":"10.1109\/QoMEX.2018.8463418"},{"key":"1857_CR24","doi-asserted-by":"crossref","unstructured":"Pan J, Sayrol E, Nieto XG, McGuinness K, O\u2019Connor NE (2016) Shallow and deep convolutional networks for saliency prediction. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 598\u2013606","DOI":"10.1109\/CVPR.2016.71"},{"key":"1857_CR25","unstructured":"Pan J, Sayrol E, Nieto XG, Ferrer CC, Torres J, McGuinness K, O\u2019Connor NE (2017) Salgan: visual saliency prediction with adversarial networks. In: CVPR scene understanding workshop (SUNw)"},{"issue":"18","key":"1857_CR26","doi-asserted-by":"publisher","first-page":"2397","DOI":"10.1016\/j.visres.2005.03.019","volume":"45","author":"RJ Peters","year":"2005","unstructured":"Peters RJ, Iyer A, Itti L, Koch C (2005) Components of bottom-up gaze allocation in natural images. Vis Res 45(18):2397\u2013 2416","journal-title":"Vis Res"},{"key":"1857_CR27","doi-asserted-by":"crossref","unstructured":"Rai Y, Guti\u00e9rrez J, Le Callet P (2017) A dataset of head and eye movements for 360 degree images. In: Proceedings of the 8th ACM on multimedia systems conference. ACM, pp 205\u2013210","DOI":"10.1145\/3083187.3083218"},{"key":"1857_CR28","doi-asserted-by":"crossref","unstructured":"Riche N, Duvinage M, Mancas M, Gosselin B, Dutoit T (2013) Saliency and human fixations: state-of-the-art and study of comparison metrics. In: Proceedings of the IEEE international conference on computer vision, pp 1153\u20131160","DOI":"10.1109\/ICCV.2013.147"},{"issue":"4","key":"1857_CR29","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TVCG.2018.2793599","volume":"24","author":"V Sitzmann","year":"2018","unstructured":"Sitzmann V, Serrano A, Pavel A, Agrawala M, Gutierrez D, Masia B, Wetzstein G (2018) Saliency in vr: how do people explore virtual environments? IEEE Trans Visual Comput Graph 24 (4):1633\u2013 1642","journal-title":"IEEE Trans Visual Comput Graph"},{"key":"1857_CR30","first-page":"43","volume":"69","author":"M Startsev","year":"2018","unstructured":"Startsev M, Dorr M (2018) 360-aware saliency estimation with conventional image saliency predictors. Signal Process: Image Commun 69:43\u201352","journal-title":"Signal Process: Image Commun"},{"key":"1857_CR31","doi-asserted-by":"crossref","unstructured":"Upenik E, Ebrahimi T (2017) A simple method to obtain visual attention data in head mounted virtual reality. In: 2017 IEEE international conference on multimedia & expo workshops (ICMEW). IEEE, pp 73\u201378","DOI":"10.1109\/ICMEW.2017.8026231"},{"key":"1857_CR32","doi-asserted-by":"crossref","unstructured":"Wang R, Li W, Qin R, Wu JZ (2017) Blur image classification based on deep learning. In: 2017 IEEE international conference on imaging systems and techniques (IST). IEEE, pp 1\u20136","DOI":"10.1109\/IST.2017.8261503"},{"issue":"5","key":"1857_CR33","doi-asserted-by":"publisher","first-page":"2368","DOI":"10.1109\/TIP.2017.2787612","volume":"27","author":"W Wang","year":"2017","unstructured":"Wang W, Shen J (2017) Deep visual attention prediction. IEEE Trans Image Process 27 (5):2368\u20132378","journal-title":"IEEE Trans Image Process"},{"key":"1857_CR34","doi-asserted-by":"crossref","unstructured":"Xu Y, Dong Y, Wu J, Sun Z, Shi Z, Yu J, Gao S (2018) Gaze prediction in dynamic 360 immersive videos. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5333\u20135342","DOI":"10.1109\/CVPR.2018.00559"},{"key":"1857_CR35","doi-asserted-by":"crossref","unstructured":"Zhai M, Chen L, Mori G, Roshtkhari MJ (2018) Deep learning of appearance models for online object tracking. In: Proceedings of the European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-11018-5_57"},{"issue":"5","key":"1857_CR36","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1109\/TPAMI.2015.2473844","volume":"38","author":"J Zhang","year":"2015","unstructured":"Zhang J, Sclaroff S (2015) Exploiting surroundedness for saliency detection: a boolean map approach. IEEE Trans Pattern Anal Mach Intell 38(5):889\u2013902","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1857_CR37","doi-asserted-by":"crossref","unstructured":"Zhang Z, Xu Y, Yu J, Gao S (2018) Saliency detection in 360 videos. In: Proceedings of the European conference on computer vision (ECCV), pp 488\u2013503","DOI":"10.1007\/978-3-030-01234-2_30"},{"issue":"11","key":"1857_CR38","doi-asserted-by":"publisher","first-page":"3212","DOI":"10.1109\/TNNLS.2018.2876865","volume":"30","author":"Z-Q Zhao","year":"2019","unstructured":"Zhao Z-Q, Zheng P, Xu S-T, Wu X (2019) Object detection with deep learning: a review. IEEE Trans Neural Netw Learn Syst 30(11):3212\u20133232","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1857_CR39","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.sigpro.2017.12.023","volume":"69","author":"Y Zhu","year":"2018","unstructured":"Zhu Y, Zhai G, Min X (2018) The prediction of head and eye movement for 360 degree images. Signal Process: Image Commun 69:15\u201325","journal-title":"Signal Process: Image Commun"},{"key":"1857_CR40","doi-asserted-by":"crossref","unstructured":"Salvucci DD, Goldberg JH (2000) Identifying fixations and saccades in eye-tracking protocols. In: Proceedings of the 2000 symposium on eye tracking research & applications, pp 71\u201378","DOI":"10.1145\/355017.355028"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-01857-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-020-01857-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-01857-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T04:31:47Z","timestamp":1625805107000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-020-01857-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,8]]},"references-count":40,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["1857"],"URL":"https:\/\/doi.org\/10.1007\/s10489-020-01857-3","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,8]]},"assertion":[{"value":"8 January 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}