{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:43:13Z","timestamp":1767339793473,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031533013"},{"type":"electronic","value":"9783031533020"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-53302-0_21","type":"book-chapter","created":{"date-parts":[[2024,1,28]],"date-time":"2024-01-28T09:02:09Z","timestamp":1706432529000},"page":"271-278","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Facilitating the\u00a0Production of\u00a0Well-Tailored Video Summaries for\u00a0Sharing on\u00a0Social Media"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5376-7158","authenticated-orcid":false,"given":"Evlampios","family":"Apostolidis","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9470-6332","authenticated-orcid":false,"given":"Konstantinos","family":"Apostolidis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0121-4364","authenticated-orcid":false,"given":"Vasileios","family":"Mezaris","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,29]]},"reference":[{"key":"21_CR1","unstructured":"Brevify: Video Summarizer. https:\/\/devpost.com\/software\/brevify-video-summarizer. Accessed 29 Sept 2023"},{"key":"21_CR2","unstructured":"Cloudinary: Easily create engaging video summaries. https:\/\/smart-ai-transformations.cloudinary.com. Accessed Sept 2023"},{"key":"21_CR3","unstructured":"Cognitive Mill: Cognitive Computing Cloud Platform For Media And Entertainment. https:\/\/cognitivemill.com. Accessed Sept 2023"},{"key":"21_CR4","unstructured":"Eightify: Youtube Summary with ChatGPT. https:\/\/chrome.google.com\/webstore\/detail\/eightify-youtube-summary\/cdcpabkolgalpgeingbdcebojebfelgb. Accessed Sept 2023"},{"key":"21_CR5","unstructured":"Pictory: Automatically summarize long videos. https:\/\/pictory.ai\/pictory-features\/auto-summarize-long-videos. Accessed 29 Sept 2023"},{"key":"21_CR6","unstructured":"summarize.tech: AI-powered video summaries. https:\/\/www.summarize.tech. Accessed 29 Sept 2023"},{"key":"21_CR7","unstructured":"Video Highlight: the fastest way to summarize and take notes from videos. https:\/\/videohighlight.com. Accessed 29 Sept 2023"},{"key":"21_CR8","unstructured":"Video Summarizer - Summarize YouTube Videos. https:\/\/mindgrasp.ai\/video-summarizer. Accessed 29 Sept 2023"},{"key":"21_CR9","unstructured":"VidSummize - AI YouTube Summary with Chat GPT. https:\/\/chrome.google.com\/webstore\/detail\/vidsummize-ai-youtube-sum\/gidcfccogfdmkfdfmhfdmfnibafoopic. Accessed 29 Sept 2023"},{"key":"21_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1007\/978-3-030-37731-1_40","volume-title":"MultiMedia Modeling","author":"E Apostolidis","year":"2020","unstructured":"Apostolidis, E., Adamantidou, E., Metsai, A.I., Mezaris, V., Patras, I.: Unsupervised video summarization via attention-driven adversarial learning. In: Ro, Y.M., et al. (eds.) MMM 2020. LNCS, vol. 11961, pp. 492\u2013504. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-37731-1_40"},{"key":"21_CR11","doi-asserted-by":"publisher","unstructured":"Apostolidis, E., Adamantidou, E., Metsai, A.I., Mezaris, V., Patras, I.: AC-SUM-GAN: connecting actor-critic and generative adversarial networks for unsupervised video summarization. IEEE Trans. Circ. Syst. Video Technol. 31(8), 3278\u20133292 (2021). https:\/\/doi.org\/10.1109\/TCSVT.2020.3037883","DOI":"10.1109\/TCSVT.2020.3037883"},{"issue":"11","key":"21_CR12","doi-asserted-by":"publisher","first-page":"1838","DOI":"10.1109\/JPROC.2021.3117472","volume":"109","author":"E Apostolidis","year":"2021","unstructured":"Apostolidis, E., Adamantidou, E., Metsai, A.I., Mezaris, V., Patras, I.: Video summarization using deep neural networks: a survey. Proc. IEEE 109(11), 1838\u20131863 (2021). https:\/\/doi.org\/10.1109\/JPROC.2021.3117472","journal-title":"Proc. IEEE"},{"key":"21_CR13","doi-asserted-by":"crossref","unstructured":"Apostolidis, K., Mezaris, V.: A fast smart-cropping method and dataset for video retargeting. In: Proceedings of the IEEE International Conference on Image Processing (ICIP), pp. 1956\u20131960 (2021)","DOI":"10.1109\/ICIP42928.2021.9506390"},{"key":"21_CR14","doi-asserted-by":"crossref","unstructured":"Apostolidis, K., Mezaris, V.: A web service for video smart-cropping. In: 2021 IEEE International Symposium on Multimedia (ISM), pp. 25\u201326. IEEE (2021)","DOI":"10.1109\/ISM52913.2021.00011"},{"key":"21_CR15","unstructured":"Awad, G., et al.: TRECVID 2017: evaluating ad-hoc and instance video search, events detection, video captioning and hyperlinking. In: 2017 TREC Video Retrieval Evaluation, TRECVID 2017, Gaithersburg, MD, USA, 13\u201315 November 2017. National Institute of Standards and Technology (NIST) (2017)"},{"key":"21_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1007\/978-3-319-23192-1_67","volume-title":"Computer Analysis of Images and Patterns","author":"L Baraldi","year":"2015","unstructured":"Baraldi, L., Grana, C., Cucchiara, R.: Shot and scene detection via hierarchical clustering for re-using broadcast video. In: Azzopardi, G., Petkov, N. (eds.) CAIP 2015. LNCS, vol. 9256, pp. 801\u2013811. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-23192-1_67"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Collyda, C., Apostolidis, K., Apostolidis, E., Adamantidou, E., Metsai, A.I., Mezaris, V.: A web service for video summarization. In: ACM International Conference on Interactive Media Experiences (IMX), pp. 148\u2013153 (2020)","DOI":"10.1145\/3391614.3399391"},{"key":"21_CR18","doi-asserted-by":"crossref","unstructured":"De Avila, S.E.F., Lopes, A.P.B., da Luz Jr, A., de Albuquerque Ara\u00fajo, A.: VSUMM: a mechanism designed to produce static video summaries and a novel evaluation method. Pattern Recogn. Lett. 32(1), 56\u201368 (2011)","DOI":"10.1016\/j.patrec.2010.08.004"},{"key":"21_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1007\/978-3-319-10584-0_33","volume-title":"Computer Vision \u2013 ECCV 2014","author":"M Gygli","year":"2014","unstructured":"Gygli, M., Grabner, H., Riemenschneider, H., Van Gool, L.: Creating summaries from user videos. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8695, pp. 505\u2013520. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10584-0_33"},{"key":"21_CR20","doi-asserted-by":"crossref","unstructured":"He, X., et al.: Unsupervised video summarization with attentive conditional generative adversarial networks. In: Proceedings of the 27th ACM International Conference on Multimedia (MM 2019), pp. 2296\u20132304. ACM, New York, NY, USA (2019)","DOI":"10.1145\/3343031.3351056"},{"key":"21_CR21","doi-asserted-by":"crossref","unstructured":"Hu, F., et al.: TinyHD: efficient video saliency prediction with heterogeneous decoders using hierarchical maps distillation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2051\u20132060 (2023)","DOI":"10.1109\/WACV56688.2023.00209"},{"key":"21_CR22","doi-asserted-by":"publisher","first-page":"107677","DOI":"10.1016\/j.patcog.2020.107677","volume":"111","author":"P Li","year":"2021","unstructured":"Li, P., Ye, Q., Zhang, L., Yuan, L., Xu, X., Shao, L.: Exploring global diverse attention via pairwise temporal relation for video summarization. Pattern Recogn. 111, 107677 (2021)","journal-title":"Pattern Recogn."},{"key":"21_CR23","doi-asserted-by":"publisher","first-page":"108840","DOI":"10.1016\/j.patcog.2022.108840","volume":"131","author":"G Liang","year":"2022","unstructured":"Liang, G., Lv, Y., Li, S., Zhang, S., Zhang, Y.: Video summarization with a convolutional attentive adversarial network. Pattern Recogn. 131, 108840 (2022)","journal-title":"Pattern Recogn."},{"key":"21_CR24","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1109\/TIP.2022.3143699","volume":"31","author":"T Liu","year":"2022","unstructured":"Liu, T., Meng, Q., Huang, J.J., Vlontzos, A., Rueckert, D., Kainz, B.: Video summarization through reinforcement learning with a 3D spatio-temporal U-Net. Trans. Image Proc. 31, 1573\u20131586 (2022)","journal-title":"Trans. Image Proc."},{"key":"21_CR25","doi-asserted-by":"publisher","first-page":"40489","DOI":"10.1007\/s11042-022-12901-4","volume":"81","author":"H Min","year":"2022","unstructured":"Min, H., Ruimin, H., Zhongyuan, W., Zixiang, X., Rui, Z.: Spatiotemporal two-stream LSTM network for unsupervised video summarization. Multimed. Tools Appl. 81, 40489\u201340510 (2022)","journal-title":"Multimed. Tools Appl."},{"key":"21_CR26","doi-asserted-by":"publisher","unstructured":"Phaphuangwittayakul, A., Guo, Y., Ying, F., Xu, W., Zheng, Z.: Self-attention recurrent summarization network with reinforcement learning for video summarization task. In: Proceedings of the 2021 IEEE International Conference on Multimedia and Expo (ICME), pp. 1\u20136 (2021). https:\/\/doi.org\/10.1109\/ICME51207.2021.9428142","DOI":"10.1109\/ICME51207.2021.9428142"},{"key":"21_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1007\/978-3-030-01258-8_22","volume-title":"Computer Vision \u2013 ECCV 2018","author":"M Rochan","year":"2018","unstructured":"Rochan, M., Ye, L., Wang, Y.: Video summarization using fully convolutional sequence networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11216, pp. 358\u2013374. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01258-8_22"},{"key":"21_CR28","doi-asserted-by":"publisher","unstructured":"Song, Y., Vallmitjana, J., Stent, A., Jaimes, A.: TVSum: summarizing web videos using titles. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5179\u20135187 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7299154","DOI":"10.1109\/CVPR.2015.7299154"},{"key":"21_CR29","unstructured":"Sou\u010dek, T., Loko\u010d, J.: Transnet V2: an effective deep network architecture for fast shot transition detection. arXiv preprint arXiv:2008.04838 (2020)"},{"key":"21_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1007\/978-3-030-20887-5_36","volume-title":"Computer Vision \u2013 ACCV 2018","author":"S Tang","year":"2019","unstructured":"Tang, S., Feng, L., Kuang, Z., Chen, Y., Zhang, W.: Fast video shot transition localization with deep structured models. In: Jawahar, C.V., Li, H., Mori, G., Schindler, K. (eds.) ACCV 2018. LNCS, vol. 11361, pp. 577\u2013592. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-20887-5_36"},{"key":"21_CR31","doi-asserted-by":"publisher","first-page":"2793","DOI":"10.1109\/TPAMI.2021.3072117","volume":"44","author":"B Zhao","year":"2021","unstructured":"Zhao, B., Li, H., Lu, X., Li, X.: Reconstructive sequence-graph network for video summarization. IEEE Trans. Pattern Anal. Mach. Intell. 44, 2793\u20132801 (2021). https:\/\/doi.org\/10.1109\/TPAMI.2021.3072117","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-53302-0_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T11:59:19Z","timestamp":1709812759000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-53302-0_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031533013","9783031533020"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-53302-0_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"29 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 January 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"ConfTool Pro","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"297","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"112","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}