{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:17:44Z","timestamp":1772039864930,"version":"3.50.1"},"publisher-location":"Cham","reference-count":59,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031729669","type":"print"},{"value":"9783031729676","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"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\/978-3-031-72967-6_7","type":"book-chapter","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T19:06:51Z","timestamp":1730574411000},"page":"109-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learned HDR Image Compression for\u00a0Perceptually Optimal Storage and\u00a0Display"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7463-0409","authenticated-orcid":false,"given":"Peibei","family":"Cao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8093-9648","authenticated-orcid":false,"given":"Haoyu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jingzhe","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Yu-Chieh","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Zhiyong","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Haiqing","family":"Bai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8608-1128","authenticated-orcid":false,"given":"Kede","family":"Ma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,3]]},"reference":[{"key":"7_CR1","unstructured":"Agustsson, E., et al.: Soft-to-hard vector quantization for end-to-end learning compressible representations. In: Advances in Neural Information Processing Systems, pp. 1141\u20131151 (2017)"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Tschannen, M., Mentzer, F., Timofte, R., Gool, L.V.: Generative adversarial networks for extreme learned image compression. In: IEEE International Conference on Computer Vision, pp. 221\u2013231 (2019)","DOI":"10.1109\/ICCV.2019.00031"},{"issue":"2","key":"7_CR3","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1109\/MSP.2015.2506199","volume":"33","author":"A Artusi","year":"2016","unstructured":"Artusi, A., et al.: JPEG XT: a compression standard for HDR and WCG images [Standards in a Nutshell]. IEEE Signal Process. Mag. 33(2), 118\u2013124 (2016)","journal-title":"IEEE Signal Process. Mag."},{"key":"7_CR4","unstructured":"Ball\u00e9, J., Laparra, V., Simoncelli, E.P.: End-to-end optimized image compression. In: International Conference on Learning Representations (2017)"},{"key":"7_CR5","unstructured":"Ball\u00e9, J., Minnen, D., Singh, S., Hwang, S.J., Johnston, N.: Variational image compression with a scale hyperprior. In: International Conference on Learning Representations (2018)"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Banterle, F., Ledda, P., Debattista, K., Chalmers, A.: Inverse tone mapping. In: International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, pp. 349\u2013356 (2006)","DOI":"10.1145\/1174429.1174489"},{"key":"7_CR7","unstructured":"Bellard, F.: BPG image format (2018). https:\/\/bellard.org\/bpg. Accessed 13 July 2024"},{"key":"7_CR8","unstructured":"Bj\u00f8ntegaard, G.: Calculation of average PSNR differences between RD-curves. Input document VCEG-M33, Video Coding Experts Group, 13th VCEG Meeting, Austin, Texas, USA (2001)"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Boschetti, A., Adami, N., Leonardi, R., Okuda, M.: Flexible and effective high dynamic range image coding. In: IEEE International Conference on Image Processing, pp. 3145\u20133148 (2010)","DOI":"10.1109\/ICIP.2010.5653441"},{"issue":"10","key":"7_CR10","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1109\/TCSVT.2021.3101953","volume":"31","author":"B Bross","year":"2021","unstructured":"Bross, B., et al.: Overview of the versatile video coding (VVC) standard and its applications. IEEE Trans. Circuits Syst. Video Technol. 31(10), 3736\u20133764 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Cao, L., Jiang, A., Li, W., Wu, H., Ye, N.: OoDHDR-codec: out-of-distribution generalization for HDR image compression. In: AAAI Conference on Artificial Intelligence, pp. 158\u2013166 (2022)","DOI":"10.1609\/aaai.v36i1.19890"},{"key":"7_CR12","unstructured":"Cao, P., Le, C., Fang, Y., Ma, K.: A perceptually optimized and self-calibrated tone mapping operator. arXiv preprint arXiv:2206.09146 (2022)"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Cao, P., Mantiuk, R.K., Ma, K.: Perceptual assessment and optimization of HDR image rendering. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 22433\u201322443 (2024)","DOI":"10.1109\/CVPR52733.2024.02117"},{"issue":"1","key":"7_CR14","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1038\/nrn3136","volume":"13","author":"M Carandini","year":"2012","unstructured":"Carandini, M., Heeger, D.J.: Normalization as a canonical neural computation. Nat. Rev. Neurosci. 13(1), 51\u201362 (2012)","journal-title":"Nat. Rev. Neurosci."},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Sun, H., Takeuchi, M., Katto, J.: Learned image compression with discretized Gaussian mixture likelihoods and attention modules. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 7939\u20137948 (2020)","DOI":"10.1109\/CVPR42600.2020.00796"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Ding, K., Liu, Y., Zou, X., Wang, S., Ma, K.: Locally adaptive structure and texture similarity for image quality assessment. In: ACM International Conference on Multimedia, pp. 2483\u20132491 (2021)","DOI":"10.1145\/3474085.3475419"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Drago, F., Myszkowski, K., Annen, T., Chiba, N.: Adaptive logarithmic mapping for displaying high contrast scenes. In: Computer Graphics Forum, pp. 419\u2013426 (2003)","DOI":"10.1111\/1467-8659.00689"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high-dynamic-range images. In: Annual Conference on Computer Graphics and Interactive Techniques, pp. 257\u2013266 (2002)","DOI":"10.1145\/566570.566574"},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Garbas, J.U., Thoma, H.: Temporally coherent luminance-to-luma mapping for high dynamic range video coding with H. 264\/AVC. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 829\u2013832 (2011)","DOI":"10.1109\/ICASSP.2011.5946532"},{"key":"7_CR20","unstructured":"Google: WebP compression study (2023). https:\/\/developers.google.com\/speed\/webp\/docs\/webp_study. Accessed 13 July 2024"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Guleryuz, O.G., et al.: Sandwiched image compression: increasing the resolution and dynamic range of standard codecs. In: Picture Coding Symposium, pp. 175\u2013179 (2022)","DOI":"10.1109\/PCS56426.2022.10018084"},{"key":"7_CR22","unstructured":"Guo, Z., Zhang, Z., Feng, R., Chen, Z.: Soft then hard: rethinking the quantization in neural image compression. In: International Conference on Machine Learning, pp. 3920\u20133929 (2021)"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Han, F., Wang, J., Xiong, R., Zhu, Q., Yin, B.: HDR image compression with convolutional autoencoder. In: IEEE International Conference on Visual Communications and Image Processing, pp. 25\u201328 (2020)","DOI":"10.1109\/VCIP49819.2020.9301853"},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Hanji, P., Mantiuk, R.K., Eilertsen, G., Hajisharif, S., Unger, J.: Comparison of single image HDR reconstruction methods - the caveats of quality assessment. In: Annual Conference on Computer Graphics and Interactive Techniques, pp.\u00a01\u20138 (2022)","DOI":"10.1145\/3528233.3530729"},{"key":"7_CR25","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems, pp. 6840\u20136851 (2020)"},{"key":"7_CR26","unstructured":"Kim, M.H., Kautz, J.: Consistent tone reproduction. In: International Conference on Computer Graphics and Imaging, pp. 152\u2013159 (2008)"},{"key":"7_CR27","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"issue":"1","key":"7_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1364\/JOSA.61.000001","volume":"61","author":"EH Land","year":"1971","unstructured":"Land, E.H., McCann, J.J.: Lightness and retinex theory. J. Opt. Soc. Am. 61(1), 1\u201311 (1971)","journal-title":"J. Opt. Soc. Am."},{"issue":"9","key":"7_CR29","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1364\/JOSAA.34.001511","volume":"34","author":"V Laparra","year":"2017","unstructured":"Laparra, V., Berardino, A., Ball\u00e9, J., Simoncelli, E.P.: Perceptually optimized image rendering. J. Opt. Soc. Am. A 34(9), 1511\u20131525 (2017)","journal-title":"J. Opt. Soc. Am. A"},{"issue":"6","key":"7_CR30","doi-asserted-by":"publisher","first-page":"908","DOI":"10.1016\/j.jvcir.2012.05.009","volume":"23","author":"C Lee","year":"2012","unstructured":"Lee, C., Kim, C.S.: Rate-distortion optimized layered coding of high dynamic range videos. J. Vis. Commun. Image Represent. 23(6), 908\u2013923 (2012)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"7_CR31","doi-asserted-by":"publisher","first-page":"5805","DOI":"10.1109\/TIP.2020.2987133","volume":"29","author":"H Li","year":"2020","unstructured":"Li, H., Ma, K., Yong, H., Zhang, L.: Fast multi-scale structural patch decomposition for multi-exposure image fusion. IEEE Trans. Image Process. 29, 5805\u20135816 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"7_CR32","doi-asserted-by":"publisher","first-page":"5900","DOI":"10.1109\/TIP.2020.2985225","volume":"29","author":"M Li","year":"2020","unstructured":"Li, M., Ma, K., You, J., Zhang, D., Zuo, W.: Efficient and effective context-based convolutional entropy modeling for image compression. IEEE Trans. Image Process. 29, 5900\u20135911 (2020)","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"7_CR33","doi-asserted-by":"publisher","first-page":"3446","DOI":"10.1109\/TPAMI.2020.2983926","volume":"43","author":"M Li","year":"2021","unstructured":"Li, M., Zuo, W., Gu, S., You, J., Zhang, D.: Learning content-weighted deep image compression. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3446\u20133461 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"7_CR34","doi-asserted-by":"crossref","unstructured":"Liang, Z., Xu, J., Zhang, D., Cao, Z., Zhang, L.: A hybrid $$\\ell _1$$-$$\\ell _0$$ layer decomposition model for tone mapping. In: IEEE Conference on Computer Vison and Pattern Recognition, pp. 4758\u20134766 (2018)","DOI":"10.1109\/CVPR.2018.00500"},{"issue":"6","key":"7_CR35","doi-asserted-by":"publisher","first-page":"1558","DOI":"10.1109\/TIP.2010.2095866","volume":"20","author":"Z Mai","year":"2011","unstructured":"Mai, Z., Mansour, H., Mantiuk, R.K., Nasiopoulos, P., Ward, R., Heidrich, W.: Optimizing a tone curve for backward-compatible high dynamic range image and video compression. IEEE Trans. Image Process. 20(6), 1558\u20131571 (2011)","journal-title":"IEEE Trans. Image Process."},{"key":"7_CR36","unstructured":"Mantiuk, R.K., Hammou, D., Hanji, P.: HDR-VDP-3: a multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content. arXiv preprint arXiv:2304.13625 (2023)"},{"issue":"1","key":"7_CR37","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1080\/2151237X.2009.10129276","volume":"14","author":"RK Mantiuk","year":"2009","unstructured":"Mantiuk, R.K., Heidrich, W.: Visualizing high dynamic range images in a web browser. J. Graph. GPU Game Tools 14(1), 43\u201353 (2009)","journal-title":"J. Graph. GPU Game Tools"},{"issue":"3","key":"7_CR38","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1145\/1015706.1015794","volume":"23","author":"RK Mantiuk","year":"2004","unstructured":"Mantiuk, R.K., Krawczyk, G., Myszkowski, K., Seidel, H.P.: Perception-motivated high dynamic range video encoding. ACM Trans. Graph. 23(3), 733\u2013741 (2004)","journal-title":"ACM Trans. Graph."},{"key":"7_CR39","doi-asserted-by":"crossref","unstructured":"Mertens, T., Kautz, J., Van\u00a0Reeth, F.: Exposure fusion. In: Pacific Conference on Computer Graphics and Applications, pp. 382\u2013390. IEEE (2007)","DOI":"10.1109\/PG.2007.17"},{"issue":"4","key":"7_CR40","doi-asserted-by":"publisher","first-page":"52","DOI":"10.5594\/j18290","volume":"122","author":"S Miller","year":"2013","unstructured":"Miller, S., Nezamabadi, M., Daly, S.: Perceptual signal coding for more efficient usage of bit codes. SMPTE Motion Imaging J. 122(4), 52\u201359 (2013)","journal-title":"SMPTE Motion Imaging J."},{"key":"7_CR41","first-page":"10771","volume":"31","author":"D Minnen","year":"2018","unstructured":"Minnen, D., Ball\u00e9, J., Toderici, G.D.: Joint autoregressive and hierarchical priors for learned image compression. Adv. Neural. Inf. Process. Syst. 31, 10771\u201310780 (2018)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"7","key":"7_CR42","doi-asserted-by":"publisher","first-page":"2055","DOI":"10.1109\/TCSVT.2018.2861560","volume":"29","author":"R Mukherjee","year":"2018","unstructured":"Mukherjee, R., Debattista, K., Rogers, T.B., Bessa, M., Chalmers, A.: Uniform color space-based high dynamic range video compression. IEEE Trans. Circuits Syst. Video Technol. 29(7), 2055\u20132066 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"7_CR43","doi-asserted-by":"crossref","unstructured":"Paris, S., Hasinoff, S.W., Kautz, J.: Local Laplacian filters: edge-aware image processing with a Laplacian pyramid. In: Annual Conference on Computer Graphics and Interactive Techniques, pp. 68:1\u201368:12 (2011)","DOI":"10.1145\/1964921.1964963"},{"issue":"98","key":"7_CR44","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1109\/TIP.2019.2936649","volume":"29","author":"A Rana","year":"2020","unstructured":"Rana, A., Singh, P., Valenzise, G., Dufaux, F., Komodakis, N., Smolic, A.: Deep tone mapping operator for high dynamic range images. IEEE Trans. Image Process. 29(98), 1285\u20131298 (2020)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"7_CR45","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1109\/TVCG.2005.9","volume":"11","author":"E Reinhard","year":"2005","unstructured":"Reinhard, E., Devlin, K.: Dynamic range reduction inspired by photoreceptor physiology. IEEE Trans. Visual Comput. Graphics 11(1), 13\u201324 (2005)","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"issue":"3","key":"7_CR46","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1145\/566654.566575","volume":"21","author":"E Reinhard","year":"2002","unstructured":"Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM Trans. Graph. 21(3), 267\u2013276 (2002)","journal-title":"ACM Trans. Graph."},{"key":"7_CR47","unstructured":"Theis, L., Shi, W., Cunningham, A., Husz\u00e1r, F.: Lossy image compression with compressive autoencoders. In: International Conference on Learning Representations (2017)"},{"key":"7_CR48","doi-asserted-by":"crossref","unstructured":"Toderici, G., et al.: Full resolution image compression with recurrent neural networks. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5306\u20135314 (2017)","DOI":"10.1109\/CVPR.2017.577"},{"key":"7_CR49","unstructured":"Torfason, R., Mentzer, F., Agustsson, E., Tschannen, M., Timofte, R., Van\u00a0Gool, L.: Towards image understanding from deep compression without decoding. In: International Conference on Learning Representations (2018)"},{"issue":"6","key":"7_CR50","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1109\/38.252554","volume":"13","author":"J Tumblin","year":"1993","unstructured":"Tumblin, J., Rushmeier, H.: Tone reproduction for realistic images. IEEE Comput. Graphics Appl. 13(6), 42\u201348 (1993)","journal-title":"IEEE Comput. Graphics Appl."},{"key":"7_CR51","doi-asserted-by":"crossref","unstructured":"Ward, G., Simmons, M.: JPEG-HDR: a backwards-compatible, high dynamic range extension to JPEG. In: Annual Conference on Computer Graphics and Interactive Techniques, pp. 3\u201310 (2006)","DOI":"10.1145\/1185657.1185685"},{"issue":"6","key":"7_CR52","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1109\/MCG.2005.133","volume":"25","author":"R Xu","year":"2005","unstructured":"Xu, R., Pattanaik, S.N., Hughes, C.E.: High-dynamic-range still-image encoding in JPEG 2000. IEEE Comput. Graphics Appl. 25(6), 57\u201364 (2005)","journal-title":"IEEE Comput. Graphics Appl."},{"key":"7_CR53","unstructured":"Yang, J., Liu, Z., Lin, M., Yanushkevich, S., Yadid-Pecht, O.: Deep reformulated Laplacian tone mapping. arXiv preprint arXiv:2102.00348 (2021)"},{"key":"7_CR54","unstructured":"Yang, R., Mandt, S.: Lossy image compression with conditional diffusion models. In: Advances in Neural Information Processing Systems, pp. 64971 \u2013 64995 (2023)"},{"issue":"2","key":"7_CR55","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1109\/TIP.2012.2221725","volume":"22","author":"H Yeganeh","year":"2013","unstructured":"Yeganeh, H., Wang, Z.: Objective quality assessment of tone-mapped images. IEEE Trans. Image Process. 22(2), 657\u2013667 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"7_CR56","doi-asserted-by":"crossref","unstructured":"Zaid, A.O., Houimli, A.: HDR image compression with optimized JPEG coding. In: European Signal Processing Conference, pp. 1539\u20131543 (2017)","DOI":"10.23919\/EUSIPCO.2017.8081467"},{"key":"7_CR57","first-page":"5822","volume":"34","author":"S Zhang","year":"2021","unstructured":"Zhang, S., Kang, N., Ryder, T., Li, Z.: iFlow: numerically invertible flows for efficient lossless compression via a uniform coder. Adv. Neural. Inf. Process. Syst. 34, 5822\u20135833 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"5","key":"7_CR58","doi-asserted-by":"publisher","first-page":"5953","DOI":"10.1364\/OE.380555","volume":"28","author":"X Zhang","year":"2020","unstructured":"Zhang, X., Yang, K., Zhou, J., Li, Y.: Retina inspired tone mapping method for high dynamic range images. Opt. Express 28(5), 5953\u20135964 (2020)","journal-title":"Opt. Express"},{"key":"7_CR59","unstructured":"Zhu, Y., Yang, Y., Cohen, T.: Transformer-based transform coding. In: International Conference on Learning Representations (2022)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72967-6_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T19:13:51Z","timestamp":1730574831000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72967-6_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,3]]},"ISBN":["9783031729669","9783031729676"],"references-count":59,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72967-6_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,3]]},"assertion":[{"value":"3 November 2024","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":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}