{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:27:36Z","timestamp":1760171256164,"version":"3.40.3"},"publisher-location":"Cham","reference-count":53,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031198410"},{"type":"electronic","value":"9783031198427"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-19842-7_41","type":"book-chapter","created":{"date-parts":[[2022,10,22]],"date-time":"2022-10-22T12:12:59Z","timestamp":1666440779000},"page":"710-726","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Video Dialog as\u00a0Conversation About Objects Living in\u00a0Space-Time"],"prefix":"10.1007","author":[{"given":"Hoang-Anh","family":"Pham","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thao Minh","family":"Le","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vuong","family":"Le","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tu Minh","family":"Phuong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Truyen","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,23]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Alamri, H., et al.: Audio visual scene-aware dialog. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7558\u20137567 (2019)","DOI":"10.1109\/CVPR.2019.00774"},{"key":"41_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/978-3-030-01261-8_7","volume-title":"Computer Vision \u2013 ECCV 2018","author":"F Baradel","year":"2018","unstructured":"Baradel, F., Neverova, N., Wolf, C., Mille, J., Mori, G.: Object level visual reasoning in videos. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11217, pp. 106\u2013122. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01261-8_7"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Carreira, J., Zisserman, A.: Quo Vadis, action recognition? A new model and the kinetics dataset. In: CVPR, pp. 6299\u20136308 (2017)","DOI":"10.1109\/CVPR.2017.502"},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Chao, Y.W., Vijayanarasimhan, S., Seybold, B., Ross, D.A., Deng, J., Sukthankar, R.: Rethinking the faster R-CNN architecture for temporal action localization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1130\u20131139 (2018)","DOI":"10.1109\/CVPR.2018.00124"},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Cho, K., Van Merri\u00ebnboer, B., Bahdanau, D., Bengio, Y.: On the properties of neural machine translation: encoder-decoder approaches. arXiv preprint arXiv:1409.1259 (2014)","DOI":"10.3115\/v1\/W14-4012"},{"key":"41_CR6","unstructured":"Chu, Y.W., Lin, K.Y., Hsu, C.C., Ku, L.W.: Multi-step joint-modality attention network for scene-aware dialogue system. arXiv preprint arXiv:2001.06206 (2020)"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Dang, L.H., Le, T.M., Le, V., Tran, T.: Hierarchical object-oriented spatio-temporal reasoning for video question answering. In: IJCAI (2021)","DOI":"10.24963\/ijcai.2021\/88"},{"issue":"5","key":"41_CR8","doi-asserted-by":"publisher","first-page":"1242","DOI":"10.1109\/TPAMI.2018.2828437","volume":"41","author":"A Das","year":"2019","unstructured":"Das, A., et al.: Visual Dialog. IEEE Trans. Pattern Anal. Mach. Intell. 41(5), 1242\u20131256 (2019). https:\/\/doi.org\/10.1109\/TPAMI.2018.2828437","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"41_CR9","doi-asserted-by":"crossref","unstructured":"Desta, M.T., Chen, L., Kornuta, T.: Object-based reasoning in VQA. In: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1814\u20131823. IEEE (2018)","DOI":"10.1109\/WACV.2018.00201"},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"Gao, S., Sethi, A., Agarwal, S., Chung, T., Hakkani-Tur, D.: Dialog state tracking: a neural reading comprehension approach. In: Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, pp. 264\u2013273 (2019)","DOI":"10.18653\/v1\/W19-5932"},{"issue":"12","key":"41_CR11","doi-asserted-by":"publisher","first-page":"3618","DOI":"10.1073\/pnas.1422953112","volume":"112","author":"D Geman","year":"2015","unstructured":"Geman, D., Geman, S., Hallonquist, N., Younes, L.: Visual turing test for computer vision systems. Proc. Natl. Acad. Sci. 112(12), 3618\u20133623 (2015)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"Geng, S., et al.: Dynamic graph representation learning for video dialog via multi-modal shuffled transformers. In: Proceedings of AAAI Conference on Artificial Intelligence (2021)","DOI":"10.1609\/aaai.v35i2.16231"},{"key":"41_CR13","doi-asserted-by":"crossref","unstructured":"Hong, Y., Wu, Q., Qi, Y., Rodriguez-Opazo, C., Gould, S.: VLN BERT: a recurrent vision-and-language BERT for navigation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1643\u20131653, June 2021","DOI":"10.1109\/CVPR46437.2021.00169"},{"key":"41_CR14","doi-asserted-by":"crossref","unstructured":"Hori, C., et al.: End-to-end audio visual scene-aware dialog using multimodal attention-based video features. In: ICASSP 2019\u20132019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2352\u20132356. IEEE (2019)","DOI":"10.1109\/ICASSP.2019.8682583"},{"key":"41_CR15","doi-asserted-by":"crossref","unstructured":"Hori, C., Cherian, A., Marks, T.K., Hori, T.: Joint student-teacher learning for audio-visual scene-aware dialog. In: INTERSPEECH, pp. 1886\u20131890 (2019)","DOI":"10.21437\/Interspeech.2019-3143"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Huang, D., Chen, P., Zeng, R., Du, Q., Tan, M., Gan, C.: Location-aware graph convolutional networks for video question answering. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 11021\u201311028 (2020)","DOI":"10.1609\/aaai.v34i07.6737"},{"key":"41_CR17","doi-asserted-by":"crossref","unstructured":"Kalogeiton, V., Weinzaepfel, P., Ferrari, V., Schmid, C.: Action tubelet detector for spatio-temporal action localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4405\u20134413 (2017)","DOI":"10.1109\/ICCV.2017.472"},{"key":"41_CR18","doi-asserted-by":"crossref","unstructured":"Kim, J., Yoon, S., Kim, D., Yoo, C.D.: Structured co-reference graph attention for video-grounded dialogue. In: AAAI (2021)","DOI":"10.1609\/aaai.v35i2.16273"},{"key":"41_CR19","unstructured":"Kim, S., et al.: The eighth dialog system technology challenge. arXiv preprint arXiv:1911.06394 (2019)"},{"key":"41_CR20","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations (ICLR) (2014)"},{"key":"41_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1007\/978-3-030-01267-0_10","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Kottur","year":"2018","unstructured":"Kottur, S., Moura, J.M.F., Parikh, D., Batra, D., Rohrbach, M.: Visual coreference resolution in visual dialog using neural module networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11219, pp. 160\u2013178. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01267-0_10"},{"key":"41_CR22","unstructured":"Le, H., Chen, N.F.: Multimodal transformer with pointer network for the DSTC8 AVSD challenge. arXiv preprint arXiv:2002.10695 (2020)"},{"key":"41_CR23","unstructured":"Le, H., Chen, N.F., Hoi, S.C.: Learning reasoning paths over semantic graphs for video-grounded dialogues. arXiv preprint arXiv:2103.00820 (2021)"},{"key":"41_CR24","unstructured":"Le, H., Hoi, S., Sahoo, D., Chen, N.: End-to-end multimodal dialog systems with hierarchical multimodal attention on video features. In: DSTC7 at AAAI2019 Workshop (2019)"},{"key":"41_CR25","doi-asserted-by":"crossref","unstructured":"Le, H., Sahoo, D., Chen, N., Hoi, S.: Multimodal transformer networks for end-to-end video-grounded dialogue systems. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5612\u20135623 (2019)","DOI":"10.18653\/v1\/P19-1564"},{"key":"41_CR26","doi-asserted-by":"crossref","unstructured":"Le, H., Sahoo, D., Chen, N., Hoi, S.C.: BiST: bi-directional spatio-temporal reasoning for video-grounded Dialogues. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1846\u20131859 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.145"},{"key":"41_CR27","doi-asserted-by":"crossref","unstructured":"Le, T.M., Le, V., Venkatesh, S., Tran, T.: Dynamic language binding in relational visual reasoning. In: IJCAI, pp. 818\u2013824 (2020)","DOI":"10.24963\/ijcai.2020\/114"},{"key":"41_CR28","doi-asserted-by":"crossref","unstructured":"Le, T.M., Le, V., Venkatesh, S., Tran, T.: Hierarchical conditional relation networks for video question answering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9972\u20139981 (2020)","DOI":"10.1109\/CVPR42600.2020.00999"},{"key":"41_CR29","unstructured":"Lee, H., Yoon, S., Dernoncourt, F., Kim, D.S., Bui, T., Jung, K.: DSTC8-AVSD: multimodal semantic transformer network with retrieval style word generator. arXiv preprint arXiv:2004.08299 (2020)"},{"key":"41_CR30","unstructured":"Lin, K.Y., Hsu, C.C., Chen, Y.N., Ku, L.W.: Entropy-enhanced multimodal attention model for scene-aware dialogue generation. arXiv preprint arXiv:1908.08191 (2019)"},{"key":"41_CR31","unstructured":"Loshchilov, I., Hutter, F.: SGDR: stochastic gradient descent with warm restarts. In: International Conference on Learning Representations (2017)"},{"key":"41_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1007\/978-3-030-58523-5_20","volume-title":"Computer Vision \u2013 ECCV 2020","author":"V Murahari","year":"2020","unstructured":"Murahari, V., Batra, D., Parikh, D., Das, A.: Large-scale pretraining for visual dialog: a simple state-of-the-art baseline. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12363, pp. 336\u2013352. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58523-5_20"},{"key":"41_CR33","unstructured":"Nguyen, D.T., Sharma, S., Schulz, H., Asri, L.E.: From film to video: multi-turn question answering with multi-modal context. In: DSTC7 Workshop at AAAI 2019 (2019)"},{"key":"41_CR34","doi-asserted-by":"crossref","unstructured":"Pan, B., et al.: Spatio-temporal graph for video captioning with knowledge distillation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10870\u201310879 (2020)","DOI":"10.1109\/CVPR42600.2020.01088"},{"key":"41_CR35","unstructured":"Sanabria, R., Palaskar, S., Metze, F.: CMU Sinbad\u2019s submission for the DSTC7 AVSD challenge. In: DSTC7 at AAAI2019 Workshop, vol. 6 (2019)"},{"key":"41_CR36","unstructured":"Seo, P.H., Lehrmann, A., Han, B., Sigal, L.: Visual reference resolution using attention memory for visual dialog. arXiv preprint arXiv:1709.07992 (2017)"},{"key":"41_CR37","doi-asserted-by":"crossref","unstructured":"Serban, I., et al.: A hierarchical latent variable encoder-decoder model for generating dialogues. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 31 (2017)","DOI":"10.1609\/aaai.v31i1.10983"},{"key":"41_CR38","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1007\/978-3-319-46448-0_31","volume-title":"Computer Vision \u2013 ECCV 2016","author":"GA Sigurdsson","year":"2016","unstructured":"Sigurdsson, G.A., Varol, G., Wang, X., Farhadi, A., Laptev, I., Gupta, A.: Hollywood in homes: crowdsourcing data collection for activity understanding. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 510\u2013526. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_31"},{"issue":"1","key":"41_CR39","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1111\/j.1467-7687.2007.00569.x","volume":"10","author":"ES Spelke","year":"2007","unstructured":"Spelke, E.S., Kinzler, K.D.: Core knowledge. Dev. Sci. 10(1), 89\u201396 (2007)","journal-title":"Dev. Sci."},{"key":"41_CR40","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"41_CR41","unstructured":"Vinyals, O., Fortunato, M., Jaitly, N.: Pointer networks. In: Advances in Neural Information Processing Systems 28 (2015)"},{"key":"41_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/978-3-030-01228-1_25","volume-title":"Computer Vision \u2013 ECCV 2018","author":"X Wang","year":"2018","unstructured":"Wang, X., Gupta, A.: Videos as space-time region graphs. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11209, pp. 413\u2013431. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01228-1_25"},{"key":"41_CR43","doi-asserted-by":"crossref","unstructured":"Wang, Y., Joty, S., Lyu, M.R., King, I., Xiong, C., Hoi, S.C.: VD-BERT: a unified vision and dialog transformer with BERT. arXiv preprint arXiv:2004.13278 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.269"},{"key":"41_CR44","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. In: ICIP, pp. 3645\u20133649. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"41_CR45","unstructured":"Xie, H., Iacobacci, I.: Audio visual scene-aware dialog system using dynamic memory networks. In: DSTC8 at AAAI2020 Workshop (2020)"},{"key":"41_CR46","doi-asserted-by":"crossref","unstructured":"Xie, S., Girshick, R., Doll\u00e1r, P., Tu, Z., He, K.: Aggregated residual transformations for deep neural networks. In: CVPR, pp. 1492\u20131500 (2017)","DOI":"10.1109\/CVPR.2017.634"},{"key":"41_CR47","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1007\/978-3-030-01267-0_19","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Xie","year":"2018","unstructured":"Xie, S., Sun, C., Huang, J., Tu, Z., Murphy, K.: Rethinking spatiotemporal feature learning: speed-accuracy trade-offs in video classification. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11219, pp. 318\u2013335. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01267-0_19"},{"key":"41_CR48","doi-asserted-by":"crossref","unstructured":"Yang, Z., Garcia, N., Chu, C., Otani, M., Nakashima, Y., Takemura, H.: BERT representations for video question answering. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 1556\u20131565 (2020)","DOI":"10.1109\/WACV45572.2020.9093596"},{"key":"41_CR49","unstructured":"Yeh, Y.T., Lin, T.C., Cheng, H.H., Deng, Y.H., Su, S.Y., Chen, Y.N.: Reactive multi-stage feature fusion for multimodal dialogue modeling. arXiv preprint arXiv:1908.05067 (2019)"},{"key":"41_CR50","unstructured":"Yi, K., et al.: CLEVRER: collision events for video representation and reasoning. arXiv preprint arXiv:1910.01442 (2019)"},{"key":"41_CR51","unstructured":"Yoshino, K., et al.: Dialog system technology challenge 7. arXiv preprint arXiv:1901.03461 (2019)"},{"key":"41_CR52","doi-asserted-by":"crossref","unstructured":"Zeng, R., et al.: Graph convolutional networks for temporal action localization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7094\u20137103 (2019)","DOI":"10.1109\/ICCV.2019.00719"},{"key":"41_CR53","doi-asserted-by":"crossref","unstructured":"Zhuge, M., et al.: Kaleido-BERT: vision-language pre-training on fashion domain. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12647\u201312657, June 2021","DOI":"10.1109\/CVPR46437.2021.01246"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19842-7_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T10:15:50Z","timestamp":1728209750000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19842-7_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031198410","9783031198427"],"references-count":53,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19842-7_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"23 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","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":"1645","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":"28% - 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":"3.21","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":"3.91","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)"}}]}}