{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T08:06:59Z","timestamp":1759565219461,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031200670"},{"type":"electronic","value":"9783031200687"}],"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\/978-3-031-20068-7_26","type":"book-chapter","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T08:06:38Z","timestamp":1668067598000},"page":"454-469","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Estimating Spatially-Varying Lighting in\u00a0Urban Scenes with\u00a0Disentangled Representation"],"prefix":"10.1007","author":[{"given":"Jiajun","family":"Tang","sequence":"first","affiliation":[]},{"given":"Yongjie","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Haoyu","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jun Hoong","family":"Chan","sequence":"additional","affiliation":[]},{"given":"Si","family":"Li","sequence":"additional","affiliation":[]},{"given":"Boxin","family":"Shi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"26_CR1","unstructured":"ambientCG, public domain materials for physically based rendering. [licensed under CC0 1.0 universal]. https:\/\/ambientcg.com"},{"key":"26_CR2","unstructured":"Blender SceneCity. https:\/\/www.cgchan.com\/store\/scenecity"},{"key":"26_CR3","unstructured":"Poly Haven, The Public 3D Asset Library. [licensed under CC0 1.0 universal]. https:\/\/polyhaven.com"},{"key":"26_CR4","unstructured":"The Stanford 3D Scanning Repository. http:\/\/graphics.stanford.edu\/data\/3Dscanrep\/"},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Malik, J.: Intrinsic scene properties from a single RGB-D image. In: Proceedings of Computer Vision and Pattern Recognition (2013)","DOI":"10.1109\/CVPR.2013.10"},{"key":"26_CR6","unstructured":"Burley, B.: Physically-based shading at Disney. In: SIGGRAPH Course: Practical Physically Based Shading in Film and Game Production (2012)"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Cheng, D., Shi, J., Chen, Y., Deng, X., Zhang, X.: Learning scene illumination by pairwise photos from rear and front mobile cameras. Comput. Graph. Forum, 37(7), 213\u2013221 (2018)","DOI":"10.1111\/cgf.13561"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Debevec, P.: Rendering synthetic objects into real scenes: bridging traditional and image-based graphics with global illumination and high dynamic range photography. In: Proceedings of ACM SIGGRAPH (1998)","DOI":"10.1145\/280814.280864"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Gardner, M.A., Hold-Geoffroy, Y., Sunkavalli, K., Gagn\u00e9, C., Lalonde, J.F.: Deep parametric indoor lighting estimation. In: Proceedings of International Conference on Computer Vision (2019)","DOI":"10.1109\/ICCV.2019.00727"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Garon, M., Sunkavalli, K., Hadap, S., Carr, N., Lalonde, J.F.: Fast spatially-varying indoor lighting estimation. In: Proceedings of Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00707"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Hold-Geoffroy, Y., Athawale, A., Lalonde, J.F.: Deep sky modeling for single image outdoor lighting estimation. In: Proceedings of Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00709"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Hold-Geoffroy, Y., Sunkavalli, K., Hadap, S., Gambaretto, E., Lalonde, J.F.: Deep outdoor illumination estimation. In: Proceedings of Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.255"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Hosek, L., Wilkie, A.: An analytic model for full spectral sky-dome radiance. ACM Trans. Graph. (TOG) 31(4), 1\u20139 (2012)","DOI":"10.1145\/2185520.2185591"},{"issue":"3","key":"26_CR14","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/MCG.2013.18","volume":"33","author":"L Hosek","year":"2013","unstructured":"Hosek, L., Wilkie, A.: Adding a solar-radiance function to the Ho\u0161ek-Wilkie skylight model. IEEE Comput. Graphics Appl. 33(3), 44\u201352 (2013)","journal-title":"IEEE Comput. Graphics Appl."},{"issue":"2","key":"26_CR15","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/s11263-011-0501-8","volume":"98","author":"JF Lalonde","year":"2012","unstructured":"Lalonde, J.F., Efros, A.A., Narasimhan, S.G.: Estimating the natural illumination conditions from a single outdoor image. Int. J. Comput. Vision 98(2), 123\u2013145 (2012)","journal-title":"Int. J. Comput. Vision"},{"key":"26_CR16","unstructured":"Lalonde, J.F., et al.: The laval HDR sky database. [free license for academic or government-sponsored researchers] (2016). http:\/\/sky.hdrdb.com"},{"key":"26_CR17","doi-asserted-by":"crossref","unstructured":"Lalonde, J.F., Matthews, I.: Lighting estimation in outdoor image collections. In: Proceedings of International Conference on 3D Vision (2014)","DOI":"10.1109\/3DV.2014.112"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"LeGendre, C., et al.: DeepLight: learning illumination for unconstrained mobile mixed reality. In: Proceedings of Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00607"},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Li, Z., Shafiei, M., Ramamoorthi, R., Sunkavalli, K., Chandraker, M.: Inverse rendering for complex indoor scenes: shape, spatially-varying lighting and SVBRDF from a single image. In: Proceedings of Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00255"},{"key":"26_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/978-3-319-46484-8_29","volume-title":"Computer Vision \u2013 ECCV 2016","author":"A Newell","year":"2016","unstructured":"Newell, A., Yang, K., Deng, J.: Stacked hourglass networks for human pose estimation. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9912, pp. 483\u2013499. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46484-8_29"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Ramamoorthi, R., Hanrahan, P.: An efficient representation for irradiance environment maps. In: Proceedings of ACM SIGGRAPH (2001)","DOI":"10.1145\/383259.383317"},{"key":"26_CR22","doi-asserted-by":"crossref","unstructured":"Saito, S., Huang, Z., Natsume, R., Morishima, S., Kanazawa, A., Li, H.: PIFu: pixel-aligned implicit function for high-resolution clothed human digitization. In: Proceedings of International Conference on Computer Vision (2019)","DOI":"10.1109\/ICCV.2019.00239"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Song, S., Funkhouser, T.: Neural illumination: lighting prediction for indoor environments. In: Proceedings of Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00708"},{"key":"26_CR24","doi-asserted-by":"crossref","unstructured":"Srinivasan, P.P., Mildenhall, B., Tancik, M., Barron, J.T., Tucker, R., Snavely, N.: Lighthouse: predicting lighting volumes for spatially-coherent illumination. In: Proceedings of Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00810"},{"key":"26_CR25","doi-asserted-by":"crossref","unstructured":"Stumpfel, J., Jones, A., Wenger, A., Tchou, C., Hawkins, T., Debevec, P.: Direct HDR capture of the sun and sky. In: Proceedings of ACM SIGGRAPH (2004)","DOI":"10.1145\/1186415.1186473"},{"key":"26_CR26","doi-asserted-by":"crossref","unstructured":"Yu, P., et al.: Hierarchical disentangled representation learning for outdoor illumination estimation and editing. In: Proceedings of International Conference on Computer Vision (2021)","DOI":"10.1109\/ICCV48922.2021.01503"},{"key":"26_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, J., Sunkavalli, K., Hold-Geoffroy, Y., Hadap, S., Eisenmann, J., Lalonde, J.F.: All-weather deep outdoor lighting estimation. In: Proceedings of Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.01040"},{"key":"26_CR28","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Zhang, Y., Li, S., Shi, B.: Spatially-varying outdoor lighting estimation from intrinsics. In: Proceedings of Computer Vision and Pattern Recognition (2021)","DOI":"10.1109\/CVPR46437.2021.01264"}],"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\/978-3-031-20068-7_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T08:18:59Z","timestamp":1668068339000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20068-7_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031200670","9783031200687"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20068-7_26","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":"11 November 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)"}}]}}