{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T14:15:43Z","timestamp":1790777743562,"version":"4.1.0"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030687953","type":"print"},{"value":"9783030687960","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-68796-0_22","type":"book-chapter","created":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T16:28:24Z","timestamp":1613838504000},"page":"305-320","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["ATSal: An Attention Based Architecture for Saliency Prediction in 360$$^\\circ $$ Videos"],"prefix":"10.1007","author":[{"given":"Yasser","family":"Dahou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marouane","family":"Tliba","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"McGuinness","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noel","family":"O\u2019Connor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,2,21]]},"reference":[{"issue":"1","key":"22_CR1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1109\/JSTSP.2020.2966864","volume":"14","author":"M Xu","year":"2020","unstructured":"Xu, M., Li, C., Zhang, S., Le Callet, P.: State-of-the-art in 360 video\/image processing: perception, assessment and compression. IEEE J. Sel. Top. Signal Process. 14(1), 5\u201326 (2020)","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"De Abreu, A., Ozcinar, C., Smolic, A.: Look around you: saliency maps for omnidirectional images in VR applications. In: 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), pp. 1\u20136. IEEE, May 2017","DOI":"10.1109\/QoMEX.2017.7965634"},{"issue":"10\u201312","key":"22_CR3","doi-asserted-by":"publisher","first-page":"1489","DOI":"10.1016\/S0042-6989(99)00163-7","volume":"40","author":"L Itti","year":"2000","unstructured":"Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Res. 40(10\u201312), 1489\u20131506 (2000)","journal-title":"Vision Res."},{"key":"22_CR4","unstructured":"Pan, J., ET AL.: SalGAN: visual saliency prediction with generative adversarial networks. arXiv preprint arXiv:1701.01081 (2017)"},{"key":"22_CR5","unstructured":"Borji, A.: Saliency prediction in the deep learning era: an empirical investigation. arXiv preprint arXiv:1810.03716. 10 (2018)"},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Xu, Y., et al.: Gaze prediction in dynamic 360 immersive videos. In: proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5333\u20135342 (2018)","DOI":"10.1109\/CVPR.2018.00559"},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Droste, R., Jiao, J., Noble, J.A.: Unified image and video saliency modeling. arXiv preprint arXiv:2003.05477 (2020)","DOI":"10.1007\/978-3-030-58558-7_25"},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Min, K., Corso, J.J.: TASED-net: temporally-aggregating spatial encoder-decoder network for video saliency detection. In Proceedings of the IEEE International Conference on Computer Vision, pp. 2394\u20132403. ISO 690 (2019)","DOI":"10.1109\/ICCV.2019.00248"},{"key":"22_CR9","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1109\/TIP.2019.2936112","volume":"29","author":"Q Lai","year":"2019","unstructured":"Lai, Q., Wang, W., Sun, H., Shen, J.: Video saliency prediction using spatiotemporal residual attentive networks. IEEE Trans. Image Process. 29, 1113\u20131126 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"22_CR10","unstructured":"Linardos, P., Mohedano, E., Nieto, J.J., O\u2019Connor, N.E., Giro-i-Nieto, X., McGuinness, K.: Simple vs complex temporal recurrences for video saliency prediction. In: British Machine Vision Conference (BMVC) (2019)"},{"key":"22_CR11","doi-asserted-by":"crossref","unstructured":"Djilali, Y.A.D., Sayah, M., McGuinness, K., O\u2019Connor, N.E.: 3DSAL: an efficient 3D-CNN architecture for video saliency prediction (2020)","DOI":"10.5220\/0008875600270036"},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Wang, W., Shen, J., Guo, F., Cheng, M.M., Borji, A.: Revisiting video saliency: A large-scale benchmark and a new model. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4894\u20134903 (2018)","DOI":"10.1109\/CVPR.2018.00514"},{"issue":"7","key":"22_CR13","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1109\/TMM.2017.2777665","volume":"20","author":"C Bak","year":"2017","unstructured":"Bak, C., Kocak, A., Erdem, E., Erdem, A.: Spatio-temporal saliency networks for dynamic saliency prediction. IEEE Trans. Multimedia 20(7), 1688\u20131698 (2017)","journal-title":"IEEE Trans. Multimedia"},{"key":"22_CR14","unstructured":"Pan, J., et al.: SalGAN: visual saliency prediction with adversarial networks. In: CVPR Scene Understanding Workshop (SUNw), July 2017"},{"issue":"1","key":"22_CR15","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.cviu.2009.09.003","volume":"114","author":"I Bogdanova","year":"2010","unstructured":"Bogdanova, I., Bur, A., H\u00fcgli, H., Farine, P.A.: Dynamic visual attention on the sphere. Comput. Vis. Image Underst. 114(1), 100\u2013110 (2010)","journal-title":"Comput. Vis. Image Underst."},{"issue":"11","key":"22_CR16","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1109\/TIP.2008.2003415","volume":"17","author":"I Bogdanova","year":"2008","unstructured":"Bogdanova, I., Bur, A., Hugli, H.: Visual attention on the sphere. IEEE Trans. Image Process. 17(11), 2000\u20132014 (2008)","journal-title":"IEEE Trans. Image Process."},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Rai, Y., Le Callet, P., Guillotel, P.: Which saliency weighting for omni directional image quality assessment?. In: 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), pp. 1\u20136. IEEE, May 2017","DOI":"10.1109\/QoMEX.2017.7965659"},{"issue":"11","key":"22_CR18","doi-asserted-by":"publisher","first-page":"2693","DOI":"10.1109\/TPAMI.2018.2858783","volume":"41","author":"M Xu","year":"2018","unstructured":"Xu, M., Song, Y., Wang, J., Qiao, M., Huo, L., Wang, Z.: Predicting head movement in panoramic video: a deep reinforcement learning approach. IEEE Trans. Pattern Anal. Mach. Intell. 41(11), 2693\u20132708 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"22_CR19","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TVCG.2018.2793599","volume":"24","author":"V Sitzmann","year":"2018","unstructured":"Sitzmann, V., et al.: Saliency in VR: how do people explore virtual environments? IEEE Trans. Visual Comput. Graphics 24(4), 1633\u20131642 (2018)","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"key":"22_CR20","doi-asserted-by":"crossref","unstructured":"Huang, X., Shen, C., Boix, X., Zhao, Q.: 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 (2015)","DOI":"10.1109\/ICCV.2015.38"},{"key":"22_CR21","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.image.2018.03.006","volume":"69","author":"P Lebreton","year":"2018","unstructured":"Lebreton, P., Raake, A.: GBVS360, BMS360, ProSal: extending existing saliency prediction models from 2D to omnidirectional images. Signal Process. Image Commun. 69, 69\u201378 (2018)","journal-title":"Signal Process. Image Commun."},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, J., Sclaroff, S.: Saliency detection: a Boolean map approach. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 153\u2013160 (2013)","DOI":"10.1109\/ICCV.2013.26"},{"key":"22_CR23","doi-asserted-by":"crossref","unstructured":"Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: Advances In Neural Information Processing Systems, pp. 545\u2013552 (2007)","DOI":"10.7551\/mitpress\/7503.003.0073"},{"key":"22_CR24","doi-asserted-by":"crossref","unstructured":"Maugey, T., Le Meur, O., Liu, Z.: Saliency-based navigation in omnidirectional image. In: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP). Luton 2017, pp. 1\u20136 (2017)","DOI":"10.1109\/MMSP.2017.8122229"},{"key":"22_CR25","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.image.2018.03.008","volume":"69","author":"F Battisti","year":"2018","unstructured":"Battisti, F., Baldoni, S., Brizzi, M., Carli, M.: A feature-based approach for saliency estimation of omni-directional images. Signal Process. Image Commun. 69, 53\u201359 (2018)","journal-title":"Signal Process. Image Commun."},{"key":"22_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.image.2018.07.009","volume":"69","author":"Y Fang","year":"2018","unstructured":"Fang, Y., Zhang, X., Imamoglu, N.: A novel superpixel-based saliency detection model for 360-degree images. Signal Process. Image Commun. 69, 1\u20137 (2018)","journal-title":"Signal Process. Image Commun."},{"key":"22_CR27","doi-asserted-by":"crossref","unstructured":"David, EJ., Guti\u00e9rrez, J., Coutrot, A., Da Silva, M. P., Callet, P.L.: A dataset of head and eye movements for 360 videos. In: Proceedings of the 9th ACM Multimedia Systems Conference, pp. 432\u2013437. ISO 690, June 2018","DOI":"10.1145\/3204949.3208139"},{"key":"22_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Xu, Y., Yu, J., Gao, S.: Saliency detection in 360 videos. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 488\u2013503 (2018)","DOI":"10.1007\/978-3-030-01234-2_30"},{"key":"22_CR29","doi-asserted-by":"crossref","unstructured":"Cheng, H.T., Chao, C.H., Dong, J.D., Wen, H.K., Liu, T.L., Sun, M.: Cube padding for weakly-supervised saliency prediction in 360 videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1420\u20131429 (2018)","DOI":"10.1109\/CVPR.2018.00154"},{"key":"22_CR30","doi-asserted-by":"crossref","unstructured":"Suzuki, T., Yamanaka, T.: Saliency map estimation for omni-directional image considering prior distributions. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2079\u20132084. IEEE, October 2018","DOI":"10.1109\/SMC.2018.00358"},{"key":"22_CR31","doi-asserted-by":"crossref","unstructured":"Lebreton, P., Fremerey, S., Raake, A.: V-BMS360: a video extention to the BMS360 image saliency model. In: 2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pp. 1\u20134. IEEE, July 2018","DOI":"10.1109\/ICMEW.2018.8551523"},{"key":"22_CR32","doi-asserted-by":"crossref","unstructured":"Nguyen, A., Yan, Z., Nahrstedt, K.: Your attention is unique: detecting 360-degree video saliency in head-mounted display for head movement prediction. In: Proceedings of the 26th ACM International Conference on Multimedia, pp. 1190\u20131198, October 2018","DOI":"10.1145\/3240508.3240669"},{"issue":"12","key":"22_CR33","doi-asserted-by":"publisher","first-page":"3544","DOI":"10.1109\/TCSVT.2018.2883305","volume":"29","author":"K Zhang","year":"2018","unstructured":"Zhang, K., Chen, Z.: Video saliency prediction based on spatial-temporal two-stream network. IEEE Trans. Circuits Syst. Video Technol. 29(12), 3544\u20133557 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"22_CR34","doi-asserted-by":"crossref","unstructured":"Hu, H.N., Lin, Y.C., Liu, M.Y., Cheng, H.T., Chang, Y.J., Sun, M.: Deep 360 pilot: learning a deep agent for piloting through 360 sports videos. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1396\u20131405. IEEE, July 2017","DOI":"10.1109\/CVPR.2017.153"},{"key":"22_CR35","doi-asserted-by":"crossref","unstructured":"Chao, F.Y., Zhang, L., Hamidouche, W., Deforges, O.: SalGAN360: visual saliency prediction on 360 degree images with generative adversarial networks. In: 2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pp. 01\u201304. IEEE, July 2018","DOI":"10.1109\/ICMEW.2018.8551543"},{"key":"22_CR36","doi-asserted-by":"crossref","unstructured":"Qiao, M., Xu, M., Wang, Z., Borji, A.: Viewport-dependent saliency prediction in 360$$^\\circ $$ video. IEEE Trans. Multimed. (2020)","DOI":"10.1109\/TMM.2020.2987682"},{"key":"22_CR37","doi-asserted-by":"crossref","unstructured":"Wang, F., et al.: Residual attention network for image classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3156\u20133164 (2017)","DOI":"10.1109\/CVPR.2017.683"},{"key":"22_CR38","doi-asserted-by":"crossref","unstructured":"Yang, Z., He, X., Gao, J., Deng, L., Smola, A.: Stacked attention networks for image question answering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 21\u201329 (2016)","DOI":"10.1109\/CVPR.2016.10"},{"key":"22_CR39","unstructured":"Tao, A., Sapra, K., Catanzaro, B.: Hierarchical multi-scale attention for semantic segmentation. arXiv preprint arXiv:2005.10821 (2020)"},{"key":"22_CR40","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Yang, Y., Wang, J., Xu, W., Yuille, A.L.: Attention to scale: Scale-aware semantic image segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3640\u20133649 (2016)","DOI":"10.1109\/CVPR.2016.396"},{"key":"22_CR41","doi-asserted-by":"crossref","unstructured":"Rai, Y., Guti\u00e9rrez, J., Le Callet, P.: A dataset of head and eye movements for 360 degree images. In: Proceedings of the 8th ACM on Multimedia Systems Conference, pp. 205\u2013210, June 2017","DOI":"10.1145\/3083187.3083218"},{"key":"22_CR42","unstructured":"Sitzmann, V., et al.: How do people explore virtual environments?. arXiv preprint arXiv:1612.04335 (2016)"},{"issue":"12","key":"22_CR43","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1016\/j.tics.2007.09.009","volume":"11","author":"A Oliva","year":"2007","unstructured":"Oliva, A., Torralba, A.: The role of context in object recognition. Trends Cogn. Sci. 11(12), 520\u2013527 (2007)","journal-title":"Trends Cogn. Sci."},{"key":"22_CR44","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"22_CR45","doi-asserted-by":"crossref","unstructured":"Bao, Y., Zhang, T., Pande, A., Wu, H., Liu, X.: Motion-prediction-based multicast for 360-degree video transmissions. In: 2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pp. 1\u20139. IEEE, June 2017","DOI":"10.1109\/SAHCN.2017.7964928"},{"issue":"3","key":"22_CR46","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1109\/TPAMI.2018.2815601","volume":"41","author":"Z Bylinskii","year":"2018","unstructured":"Bylinskii, Z., Judd, T., Oliva, A., Torralba, A., Durand, F.: What do different evaluation metrics tell us about saliency models? IEEE Trans. Pattern Anal. Mach. Intell. 41(3), 740\u2013757 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-68796-0_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T15:55:14Z","timestamp":1697903714000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-68796-0_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030687953","9783030687960"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-68796-0_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"21 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ICPR2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icpr2020.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}