{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:36:30Z","timestamp":1778085390682,"version":"3.51.4"},"publisher-location":"Singapore","reference-count":48,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819609109","type":"print"},{"value":"9789819609116","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T00:00:00Z","timestamp":1733616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T00:00:00Z","timestamp":1733616000000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-0911-6_17","type":"book-chapter","created":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T07:53:47Z","timestamp":1733558027000},"page":"284-300","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["ATTIQA: Generalizable Image Quality Feature Extractor Using Attribute-Aware Pretraining"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2154-3348","authenticated-orcid":false,"given":"Daekyu","family":"Kwon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6414-2380","authenticated-orcid":false,"given":"Dongyoung","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3809-7886","authenticated-orcid":false,"given":"Sehwan","family":"Ki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8530-9802","authenticated-orcid":false,"given":"Younghyun","family":"Jo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyong-Euk","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8512-216X","authenticated-orcid":false,"given":"Seon Joo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,8]]},"reference":[{"key":"17_CR1","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s11760-017-1166-8","volume":"12","author":"S Bianco","year":"2018","unstructured":"Bianco, S., Celona, L., Napoletano, P., Schettini, R.: On the use of deep learning for blind image quality assessment. SIViP 12, 355\u2013362 (2018)","journal-title":"SIViP"},{"issue":"1","key":"17_CR2","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/TIP.2017.2760518","volume":"27","author":"S Bosse","year":"2017","unstructured":"Bosse, S., Maniry, D., M\u00fcller, K.R., Wiegand, T., Samek, W.: Deep neural networks for no-reference and full-reference image quality assessment. IEEE Transactions on Image Processing (TIP) 27(1), 206\u2013219 (2017)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Bychkovsky, V., Paris, S., Chan, E., Durand, F.: Learning photographic global tonal adjustment with a database of input \/ output image pairs. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2011)","DOI":"10.1109\/CVPR.2011.5995332"},{"key":"17_CR4","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: Transformers for image recognition at scale. In: International Conference on Learning Representations (ICLR) (2021)"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Fang, Y., Zhu, H., Zeng, Y., Ma, K., Wang, Z.: Perceptual quality assessment of smartphone photography. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3677\u20133686 (2020)","DOI":"10.1109\/CVPR42600.2020.00373"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Gao, T., Fisch, A., Chen, D.: Making pre-trained language models better few-shot learners. In: Zong, C., Xia, F., Li, W., Navigli, R. (eds.) Proceedings of the Association for Computational Linguistics (ACL). pp. 3816\u20133830 (2021)","DOI":"10.18653\/v1\/2021.acl-long.295"},{"key":"17_CR7","unstructured":"Gao, X., Gao, F., Tao, D., Li, X.: Universal blind image quality assessment metrics via natural scene statistics and multiple kernel learning. IEEE Transactions on neural networks and learning systems (2013)"},{"issue":"1","key":"17_CR8","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/TIP.2015.2500021","volume":"25","author":"D Ghadiyaram","year":"2015","unstructured":"Ghadiyaram, D., Bovik, A.C.: Massive online crowdsourced study of subjective and objective picture quality. IEEE Transactions on Image Processing (TIP) 25(1), 372\u2013387 (2015)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Golestaneh, S.A., Dadsetan, S., Kitani, K.M.: No-reference image quality assessment via transformers, relative ranking, and self-consistency. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV). pp. 1220\u20131230 (2022)","DOI":"10.1109\/WACV51458.2022.00404"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"17_CR11","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems (NeurIPS) 33, 6840\u20136851 (2020)","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"17_CR12","doi-asserted-by":"publisher","first-page":"4041","DOI":"10.1109\/TIP.2020.2967829","volume":"29","author":"V Hosu","year":"2020","unstructured":"Hosu, V., Lin, H., Sziranyi, T., Saupe, D.: Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment. IEEE Transactions on Image Processing (TIP) 29, 4041\u20134056 (2020)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Huang, Y., Li, L., Yang, Y., Li, Y., Guo, Y.: Explainable and generalizable blind image quality assessment via semantic attribute reasoning. IEEE Transactions on Multimedia (TMM) (2022)","DOI":"10.1109\/TMM.2022.3225728"},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Kang, L., Ye, P., Li, Y., Doermann, D.: Convolutional neural networks for no-reference image quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1733\u20131740 (2014)","DOI":"10.1109\/CVPR.2014.224"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Ke, J., Wang, Q., Wang, Y., Milanfar, P., Yang, F.: Musiq: Multi-scale image quality transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 5148\u20135157 (2021)","DOI":"10.1109\/ICCV48922.2021.00510"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Ke, J., Ye, K., Yu, J., Wu, Y., Milanfar, P., Yang, F.: Vila: Learning image aesthetics from user comments with vision-language pretraining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 10041\u201310051 (2023)","DOI":"10.1109\/CVPR52729.2023.00968"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Li, C., Zhang, Z., Wu, H., Sun, W., Min, X., Liu, X., Zhai, G., Lin, W.: Agiqa-3k: An open database for ai-generated image quality assessment (2023)","DOI":"10.1109\/TCSVT.2023.3319020"},{"key":"17_CR18","unstructured":"Li, J., Li, D., Xiong, C., Hoi, S.: Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In: International conference on machine learning (ICML). pp. 12888\u201312900 (2022)"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Liu, X., Van De\u00a0Weijer, J., Bagdanov, A.D.: Rankiqa: Learning from rankings for no-reference image quality assessment. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 1040\u20131049 (2017)","DOI":"10.1109\/ICCV.2017.118"},{"key":"17_CR20","doi-asserted-by":"publisher","first-page":"4149","DOI":"10.1109\/TIP.2022.3181496","volume":"31","author":"PC Madhusudana","year":"2022","unstructured":"Madhusudana, P.C., Birkbeck, N., Wang, Y., Adsumilli, B., Bovik, A.C.: Image quality assessment using contrastive learning. IEEE Transactions on Image Processing (TIP) 31, 4149\u20134161 (2022)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"issue":"12","key":"17_CR21","doi-asserted-by":"publisher","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","volume":"21","author":"A Mittal","year":"2012","unstructured":"Mittal, A., Moorthy, A.K., Bovik, A.C.: No-reference image quality assessment in the spatial domain. IEEE Transactions on Image Processing (TIP) 21(12), 4695\u20134708 (2012)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"issue":"3","key":"17_CR22","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2012","unstructured":"Mittal, A., Soundararajan, R., Bovik, A.C.: Making a \u2018completely blind\u2019 image quality analyzer. IEEE Signal Process. Lett. 20(3), 209\u2013212 (2012)","journal-title":"IEEE Signal Process. Lett."},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Murray, N., Marchesotti, L., Perronnin, F.: Ava: A large-scale database for aesthetic visual analysis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2408\u20132415 (2012)","DOI":"10.1109\/CVPR.2012.6247954"},{"key":"17_CR24","unstructured":"Nichol, A., Dhariwal, P., Ramesh, A., Shyam, P., Mishkin, P., McGrew, B., Sutskever, I., Chen, M.: Glide: Towards photorealistic image generation and editing with text-guided diffusion models. In: International conference on machine learning (ICML) (2021)"},{"key":"17_CR25","unstructured":"OpenAI: Gpt-4 technical report (2023)"},{"key":"17_CR26","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.image.2014.10.009","volume":"30","author":"NN Ponomarenko","year":"2015","unstructured":"Ponomarenko, N.N., Jin, L., Ieremeiev, O., Lukin, V.V., Egiazarian, K.O., Astola, J., Vozel, B., Chehdi, K., Carli, M., Battisti, F., Kuo, C.C.J.: Image database tid2013: Peculiarities, results and perspectives. Signal Processing, Image Communication 30, 57\u201377 (2015)","journal-title":"Signal Processing, Image Communication"},{"key":"17_CR27","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning transferable visual models from natural language supervision. In: International conference on machine learning (ICML) (2021)"},{"key":"17_CR28","unstructured":"Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., Sutskever, I.: Zero-shot text-to-image generation. In: International conference on machine learning (ICML). pp. 8821\u20138831 (2021)"},{"key":"17_CR29","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"17_CR30","doi-asserted-by":"crossref","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M.S., Berg, A.C., Fei-Fei, L.: Imagenet large scale visual recognition challenge. International Journal of Computer Vision (IJCV) pp. 211 \u2013 252 (2014)","DOI":"10.1007\/s11263-015-0816-y"},{"issue":"8","key":"17_CR31","doi-asserted-by":"publisher","first-page":"3339","DOI":"10.1109\/TIP.2012.2191563","volume":"21","author":"MA Saad","year":"2012","unstructured":"Saad, M.A., Bovik, A.C., Charrier, C.: Blind image quality assessment: A natural scene statistics approach in the dct domain. IEEE Transactions on Image Processing (TIP) 21(8), 3339\u20133352 (2012)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"17_CR32","doi-asserted-by":"crossref","unstructured":"Saha, A., Mishra, S., Bovik, A.C.: Re-iqa: Unsupervised learning for image quality assessment in the wild. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 5846\u20135855 (2023)","DOI":"10.1109\/CVPR52729.2023.00566"},{"key":"17_CR33","doi-asserted-by":"crossref","unstructured":"Shin, U., Lee, K., Kweon, I.S.: Drl-isp: Multi-objective camera isp with deep reinforcement learning. In: IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 7044\u20137051 (2022)","DOI":"10.1109\/IROS47612.2022.9981361"},{"key":"17_CR34","unstructured":"Su, S., Hosu, V., Lin, H., Zhang, Y., Saupe, D.: Koniq++: Boosting no-reference image quality assessment in the wild by jointly predicting image quality and defects. In: British Machine Vision Conference (BMVC) (2021)"},{"key":"17_CR35","doi-asserted-by":"crossref","unstructured":"Su, S., Yan, Q., Zhu, Y., Zhang, C., Ge, X., Sun, J., Zhang, Y.: Blindly assess image quality in the wild guided by a self-adaptive hyper network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3667\u20133676 (2020)","DOI":"10.1109\/CVPR42600.2020.00372"},{"issue":"8","key":"17_CR36","doi-asserted-by":"publisher","first-page":"3998","DOI":"10.1109\/TIP.2018.2831899","volume":"27","author":"H Talebi","year":"2018","unstructured":"Talebi, H., Milanfar, P.: Nima: Neural image assessment. IEEE Transactions on Image Processing (TIP) 27(8), 3998\u20134011 (2018)","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"17_CR37","doi-asserted-by":"crossref","unstructured":"Wang, J., Chan, K.C., Loy, C.C.: Exploring clip for assessing the look and feel of images. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). vol.\u00a037, pp. 2555\u20132563 (2023)","DOI":"10.1609\/aaai.v37i2.25353"},{"key":"17_CR38","doi-asserted-by":"publisher","first-page":"4326","DOI":"10.1109\/TMM.2020.3040529","volume":"23","author":"X Yang","year":"2021","unstructured":"Yang, X., Li, F., Liu, H.: Ttl-iqa: Transitive transfer learning based no-reference image quality assessment. IEEE Transactions on Multimedia (TMM) 23, 4326\u20134340 (2021). https:\/\/doi.org\/10.1109\/TMM.2020.3040529","journal-title":"IEEE Transactions on Multimedia (TMM)"},{"key":"17_CR39","doi-asserted-by":"crossref","unstructured":"Ye, P., Kumar, J., Kang, L., Doermann, D.: Unsupervised feature learning framework for no-reference image quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1098\u20131105 (2012)","DOI":"10.1109\/CVPR.2012.6247789"},{"key":"17_CR40","doi-asserted-by":"crossref","unstructured":"Ying, Z., Niu, H., Gupta, P., Mahajan, D., Ghadiyaram, D., Bovik, A.: From patches to pictures (paq-2-piq): Mapping the perceptual space of picture quality. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3575\u20133585 (2020)","DOI":"10.1109\/CVPR42600.2020.00363"},{"key":"17_CR41","doi-asserted-by":"crossref","unstructured":"You, J., Korhonen, J.: Transformer for image quality assessment. In: IEEE International Conference on Image Processing (ICIP). pp. 1389\u20131393 (2021)","DOI":"10.1109\/ICIP42928.2021.9506075"},{"key":"17_CR42","unstructured":"Yu, J., Wang, Z., Vasudevan, V., Yeung, L., Seyedhosseini, M., Wu, Y.: Coca: Contrastive captioners are image-text foundation models (2022)"},{"key":"17_CR43","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"issue":"1","key":"17_CR44","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/TCSVT.2018.2886771","volume":"30","author":"W Zhang","year":"2018","unstructured":"Zhang, W., Ma, K., Yan, J., Deng, D., Wang, Z.: Blind image quality assessment using a deep bilinear convolutional neural network. IEEE Transactions on Circuits and Systems for Video Technology (TCVST) 30(1), 36\u201347 (2018)","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology (TCVST)"},{"key":"17_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, W., Zhai, G., Wei, Y., Yang, X., Ma, K.: Blind image quality assessment via vision-language correspondence: A multitask learning perspective. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 14071\u201314081 (2023)","DOI":"10.1109\/CVPR52729.2023.01352"},{"key":"17_CR46","doi-asserted-by":"crossref","unstructured":"Zhao, K., Yuan, K., Sun, M., Li, M., Wen, X.: Quality-aware pre-trained models for blind image quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 22302\u201322313 (2023)","DOI":"10.1109\/CVPR52729.2023.02136"},{"issue":"9","key":"17_CR47","doi-asserted-by":"publisher","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","volume":"130","author":"K Zhou","year":"2022","unstructured":"Zhou, K., Yang, J., Loy, C.C., Liu, Z.: Learning to prompt for vision-language models. International Journal of Computer Vision (IJCV) 130(9), 2337\u20132348 (2022)","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"17_CR48","doi-asserted-by":"crossref","unstructured":"Zhu, H., Li, L., Wu, J., Dong, W., Shi, G.: Metaiqa: Deep meta-learning for no-reference image quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 14143\u201314152 (2020)","DOI":"10.1109\/CVPR42600.2020.01415"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ACCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0911-6_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T08:20:34Z","timestamp":1733559634000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0911-6_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,8]]},"ISBN":["9789819609109","9789819609116"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0911-6_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,8]]},"assertion":[{"value":"8 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hanoi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","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":"8 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2024","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":"accv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}