{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:48:50Z","timestamp":1769723330372,"version":"3.49.0"},"publisher-location":"Cham","reference-count":72,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030584511","type":"print"},{"value":"9783030584528","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-58452-8_11","type":"book-chapter","created":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T00:34:03Z","timestamp":1604363643000},"page":"178-196","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Crowdsampling the Plenoptic Function"],"prefix":"10.1007","author":[{"given":"Zhengqi","family":"Li","sequence":"first","affiliation":[]},{"given":"Wenqi","family":"Xian","sequence":"additional","affiliation":[]},{"given":"Abe","family":"Davis","sequence":"additional","affiliation":[]},{"given":"Noah","family":"Snavely","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,3]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Adelson, E.H., Bergen, J.R.: The plenoptic function and the elements of early vision. In: Computational Models of Visual Processing, pp. 3\u201320. MIT Press (1991)","DOI":"10.7551\/mitpress\/2002.003.0004"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Buehler, C., Bosse, M., McMillan, L., Gortler, S., Cohen, M.: Unstructured lumigraph rendering. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 425\u2013432 (2001)","DOI":"10.1145\/383259.383309"},{"key":"11_CR3","doi-asserted-by":"publisher","unstructured":"Chai, J.X., Tong, X., Chan, S.C., Shum, H.Y.: Plenoptic sampling. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2000, pp. 307\u2013318. ACM Press\/Addison-Wesley Publishing Co., USA (2000). https:\/\/doi.org\/10.1145\/344779.344932","DOI":"10.1145\/344779.344932"},{"issue":"3","key":"11_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2487228.2487238","volume":"32","author":"G Chaurasia","year":"2013","unstructured":"Chaurasia, G., Duchene, S., Sorkine-Hornung, O., Drettakis, G.: Depth synthesis and local warps for plausible image-based navigation. ACM Trans. Graph. 32(3), 1\u201312 (2013)","journal-title":"ACM Trans. Graph."},{"key":"11_CR5","unstructured":"Chen, L.C., Papandreou, G., Schroff, F., Adam, H.: Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Q., Koltun, V.: Photographic image synthesis with cascaded refinement networks. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1511\u20131520 (2017)","DOI":"10.1109\/ICCV.2017.168"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Z., et al.: A neural rendering framework for free-viewpoint relighting. arXiv preprint arXiv:1911.11530 (2019)","DOI":"10.1109\/CVPR42600.2020.00564"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Choi, I., Gallo, O., Troccoli, A., Kim, M.H., Kautz, J.: Extreme view synthesis. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 7781\u20137790 (2019)","DOI":"10.1109\/ICCV.2019.00787"},{"key":"11_CR9","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1111\/j.1467-8659.2012.03009.x","volume":"31","author":"A Davis","year":"2012","unstructured":"Davis, A., Levoy, M., Durand, F.: Unstructured light fields. Comput. Graph. Forum 31, 305\u2013314 (2012)","journal-title":"Comput. Graph. Forum"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Debevec, P.E., Taylor, C.J., Malik, J.: Modeling and rendering architecture from photographs: a hybrid geometry-and image-based approach. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 11\u201320 (1996)","DOI":"10.1145\/237170.237191"},{"issue":"6394","key":"11_CR11","doi-asserted-by":"publisher","first-page":"1204","DOI":"10.1126\/science.aar6170","volume":"360","author":"SA Eslami","year":"2018","unstructured":"Eslami, S.A., et al.: Neural scene representation and rendering. Science 360(6394), 1204\u20131210 (2018)","journal-title":"Science"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Flynn, J., et al.: DeepView: view synthesis with learned gradient descent. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 2367\u20132376 (2019)","DOI":"10.1109\/CVPR.2019.00247"},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Flynn, J., Neulander, I., Philbin, J., Snavely, N.: DeepStereo: learning to predict new views from the world\u2019s imagery. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 5515\u20135524 (2016)","DOI":"10.1109\/CVPR.2016.595"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Garg, R., Du, H., Seitz, S.M., Snavely, N.: The dimensionality of scene appearance. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1917\u20131924. IEEE (2009)","DOI":"10.1109\/ICCV.2009.5459424"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: Proc. Computer Vision and Pattern Recognition (CVPR). pp. 2414\u20132423 (2016)","DOI":"10.1109\/CVPR.2016.265"},{"key":"11_CR16","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Gortler, S.J., Grzeszczuk, R., Szeliski, R., Cohen, M.F.: The lumigraph. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 43\u201354 (1996)","DOI":"10.1145\/237170.237200"},{"key":"11_CR18","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of Wasserstein GANs. In: Neural Information Processing Systems, pp. 5767\u20135777 (2017)"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Hauagge, D.C., Wehrwein, S., Upchurch, P., Bala, K., Snavely, N.: Reasoning about photo collections using models of outdoor illumination. In: Proceedings of the British Machine Vision Conference (BMVC) (2014)","DOI":"10.5244\/C.28.78"},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"11_CR21","doi-asserted-by":"publisher","first-page":"234:1","DOI":"10.1145\/3130800.3130828","volume":"36","author":"P Hedman","year":"2017","unstructured":"Hedman, P., Alsisan, S., Szeliski, R., Kopf, J.: Casual 3D photography. ACM Trans. Graph. 36, 234:1\u2013234:15 (2017)","journal-title":"ACM Trans. Graph."},{"issue":"6","key":"11_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3272127.3275084","volume":"37","author":"P Hedman","year":"2018","unstructured":"Hedman, P., Philip, J., Price, T., Frahm, J.M., Drettakis, G., Brostow, G.: Deep blending for free-viewpoint image-based rendering. ACM Trans. Graph. 37(6), 1\u201315 (2018)","journal-title":"ACM Trans. Graph."},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Huang, X., Belongie, S.: Arbitrary style transfer in real-time with adaptive instance normalization. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1501\u20131510 (2017)","DOI":"10.1109\/ICCV.2017.167"},{"key":"11_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/978-3-030-01219-9_11","volume-title":"Computer Vision \u2013 ECCV 2018","author":"X Huang","year":"2018","unstructured":"Huang, X., Liu, M.-Y., Belongie, S., Kautz, J.: Multimodal unsupervised image-to-image translation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11207, pp. 179\u2013196. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01219-9_11"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"issue":"6","key":"11_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2980179.2980251","volume":"35","author":"NK Kalantari","year":"2016","unstructured":"Kalantari, N.K., Wang, T.C., Ramamoorthi, R.: Learning-based view synthesis for light field cameras. ACM Trans. Graph. 35(6), 1\u201310 (2016)","journal-title":"ACM Trans. Graph."},{"key":"11_CR27","unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of GANs for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196 (2017)"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 4401\u20134410 (2019)","DOI":"10.1109\/CVPR.2019.00453"},{"key":"11_CR29","doi-asserted-by":"publisher","first-page":"202:1","DOI":"10.1145\/2366145.2366221","volume":"31","author":"PY Laffont","year":"2012","unstructured":"Laffont, P.Y., Bousseau, A., Paris, S., Durand, F., Drettakis, G.: Coherent intrinsic images from photo collections. ACM Trans. Graph. 31, 202:1\u2013202:11 (2012)","journal-title":"ACM Trans. Graph."},{"key":"11_CR30","doi-asserted-by":"crossref","unstructured":"Ledig, C., et al.: Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 4681\u20134690 (2017)","DOI":"10.1109\/CVPR.2017.19"},{"key":"11_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1007\/978-3-030-01246-5_3","volume-title":"Computer Vision \u2013 ECCV 2018","author":"H-Y Lee","year":"2018","unstructured":"Lee, H.-Y., Tseng, H.-Y., Huang, J.-B., Singh, M., Yang, M.-H.: Diverse image-to-image translation via disentangled representations. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11205, pp. 36\u201352. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01246-5_3"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Levin, A., Durand, F.: Linear view synthesis using a dimensionality gap light field prior. In: Proceedings Computer Vision and Pattern Recognition (CVPR), pp. 1831\u20131838 (2010)","DOI":"10.1109\/CVPR.2010.5539854"},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Levoy, M., Hanrahan, P.: Light field rendering. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 31\u201342 (1996)","DOI":"10.1145\/237170.237199"},{"key":"11_CR34","doi-asserted-by":"crossref","unstructured":"Li, Z., et al.: Learning the depths of moving people by watching Frozen people. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 4521\u20134530 (2019)","DOI":"10.1109\/CVPR.2019.00465"},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Li, Z., Snavely, N.: MegaDepth: learning single-view depth prediction from internet photos. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 2041\u20132050 (2018)","DOI":"10.1109\/CVPR.2018.00218"},{"issue":"4","key":"11_CR36","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1145\/3306346.3323020","volume":"38","author":"S Lombardi","year":"2019","unstructured":"Lombardi, S., Simon, T., Saragih, J., Schwartz, G., Lehrmann, A., Sheikh, Y.: Neural volumes: learning dynamic renderable volumes from images. ACM Trans. Graph. 38(4), 65 (2019)","journal-title":"ACM Trans. Graph."},{"key":"11_CR37","doi-asserted-by":"crossref","unstructured":"Mao, X., Li, Q., Xie, H., Lau, R.Y., Wang, Z., Paul Smolley, S.: Least squares generative adversarial networks. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2794\u20132802 (2017)","DOI":"10.1109\/ICCV.2017.304"},{"key":"11_CR38","doi-asserted-by":"crossref","unstructured":"Martin-Brualla, R., Gallup, D., Seitz, S.M.: 3D time-lapse reconstruction from internet photos. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1332\u20131340 (2015)","DOI":"10.1109\/ICCV.2015.157"},{"issue":"4","key":"11_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2766903","volume":"34","author":"R Martin-Brualla","year":"2015","unstructured":"Martin-Brualla, R., Gallup, D., Seitz, S.M.: Time-lapse mining from internet photos. ACM Trans. Graph. 34(4), 1\u20138 (2015)","journal-title":"ACM Trans. Graph."},{"key":"11_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1007\/978-3-319-10584-0_40","volume-title":"Computer Vision \u2013 ECCV 2014","author":"K Matzen","year":"2014","unstructured":"Matzen, K., Snavely, N.: Scene chronology. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8695, pp. 615\u2013630. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10584-0_40"},{"key":"11_CR41","doi-asserted-by":"crossref","unstructured":"Meshry, M., et al.: Neural rerendering in the wild. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 6871\u20136880 (2019)","DOI":"10.1109\/CVPR.2019.00704"},{"issue":"4","key":"11_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3322980","volume":"38","author":"B Mildenhall","year":"2019","unstructured":"Mildenhall, B., et al.: Local light field fusion: practical view synthesis with prescriptive sampling guidelines. ACM Trans. Graph. 38(4), 1\u201314 (2019)","journal-title":"ACM Trans. Graph."},{"key":"11_CR43","doi-asserted-by":"crossref","unstructured":"Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 2337\u20132346 (2019)","DOI":"10.1109\/CVPR.2019.00244"},{"issue":"6","key":"11_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3130800.3130855","volume":"36","author":"E Penner","year":"2017","unstructured":"Penner, E., Zhang, L.: Soft 3D reconstruction for view synthesis. ACM Trans. Graph. 36(6), 1\u201311 (2017)","journal-title":"ACM Trans. Graph."},{"issue":"4","key":"11_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3323013","volume":"38","author":"J Philip","year":"2019","unstructured":"Philip, J., Gharbi, M., Zhou, T., Efros, A.A., Drettakis, G.: Multi-view relighting using a geometry-aware network. ACM Trans. Graph. 38(4), 1\u201314 (2019)","journal-title":"ACM Trans. Graph."},{"key":"11_CR46","doi-asserted-by":"crossref","unstructured":"Sangkloy, P., Lu, J., Fang, C., Yu, F., Hays, J.: Scribbler: controlling deep image synthesis with sketch and color. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 5400\u20135409 (2017)","DOI":"10.1109\/CVPR.2017.723"},{"key":"11_CR47","doi-asserted-by":"crossref","unstructured":"Schonberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 4104\u20134113 (2016)","DOI":"10.1109\/CVPR.2016.445"},{"key":"11_CR48","doi-asserted-by":"crossref","unstructured":"Shan, Q., Adams, R., Curless, B., Furukawa, Y., Seitz, S.M.: The visual turing test for scene reconstruction. In: International Conference on 3D Vision (3DV), pp. 25\u201332 (2013)","DOI":"10.1109\/3DV.2013.12"},{"key":"11_CR49","doi-asserted-by":"crossref","unstructured":"Sheng, L., Lin, Z., Shao, J., Wang, X.: Avatar-net: multi-scale zero-shot style transfer by feature decoration. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 1\u20139 (2018)","DOI":"10.1109\/CVPR.2018.00860"},{"key":"11_CR50","doi-asserted-by":"publisher","first-page":"12:1","DOI":"10.1145\/2682631","volume":"34","author":"L Shi","year":"2014","unstructured":"Shi, L., Hassanieh, H., Davis, A., Katabi, D., Durand, F.: Light field reconstruction using sparsity in the continuous Fourier domain. ACM Trans. Graph. 34, 12:1\u201312:13 (2014)","journal-title":"ACM Trans. Graph."},{"key":"11_CR51","doi-asserted-by":"publisher","unstructured":"Shi, L., Hassanieh, H., Davis, A., Katabi, D., Durand, F.: Light field reconstruction using sparsity in the continuous Fourier domain. ACM Trans. Graph. 34(1) (2015). https:\/\/doi.org\/10.1145\/2682631","DOI":"10.1145\/2682631"},{"key":"11_CR52","doi-asserted-by":"crossref","unstructured":"Simon, I., Snavely, N., Seitz, S.M.: Scene summarization for online image collections. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1\u20138. IEEE (2007)","DOI":"10.1109\/ICCV.2007.4408863"},{"key":"11_CR53","doi-asserted-by":"crossref","unstructured":"Sitzmann, V., Thies, J., Heide, F., Nie\u00dfner, M., Wetzstein, G., Zollhofer, M.: DeepVoxels: learning persistent 3D feature embeddings. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 2437\u20132446 (2019)","DOI":"10.1109\/CVPR.2019.00254"},{"key":"11_CR54","unstructured":"Sitzmann, V., Zollh\u00f6fer, M., Wetzstein, G.: Scene representation networks: continuous 3D-structure-aware neural scene representations. In: Neural Information Processing Systems, pp. 1119\u20131130 (2019)"},{"key":"11_CR55","doi-asserted-by":"crossref","unstructured":"Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3D. ACM Trans. Graph. (SIGGRAPH) (2006)","DOI":"10.1145\/1141911.1141964"},{"key":"11_CR56","doi-asserted-by":"crossref","unstructured":"Srinivasan, P.P., Tucker, R., Barron, J.T., Ramamoorthi, R., Ng, R., Snavely, N.: Pushing the boundaries of view extrapolation with multiplane images. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 175\u2013184 (2019)","DOI":"10.1109\/CVPR.2019.00026"},{"key":"11_CR57","doi-asserted-by":"crossref","unstructured":"Srinivasan, P.P., Wang, T., Sreelal, A., Ramamoorthi, R., Ng, R.: Learning to synthesize a 4D RGBD light field from a single image. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2243\u20132251 (2017)","DOI":"10.1109\/ICCV.2017.246"},{"key":"11_CR58","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1023\/A:1008192912624","volume":"32","author":"R Szeliski","year":"1998","unstructured":"Szeliski, R., Golland, P.: Stereo matching with transparency and matting. Int. J. Comput. Vis. 32, 45\u201361 (1998)","journal-title":"Int. J. Comput. Vis."},{"issue":"4","key":"11_CR59","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3323035","volume":"38","author":"J Thies","year":"2019","unstructured":"Thies, J., Zollh\u00f6fer, M., Nie\u00dfner, M.: Deferred neural rendering: image synthesis using neural textures. ACM Trans. Graph. 38(4), 1\u201312 (2019)","journal-title":"ACM Trans. Graph."},{"key":"11_CR60","doi-asserted-by":"crossref","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.: Improved texture networks: maximizing quality and diversity in feed-forward stylization and texture synthesis. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 6924\u20136932 (2017)","DOI":"10.1109\/CVPR.2017.437"},{"key":"11_CR61","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1109\/TPAMI.2017.2653101","volume":"40","author":"S Vagharshakyan","year":"2015","unstructured":"Vagharshakyan, S., Bregovic, R., Gotchev, A.P.: Light field reconstruction using shearlet transform. Trans. Pattern Anal. Mach. Intell. 40, 133\u2013147 (2015)","journal-title":"Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR62","doi-asserted-by":"crossref","unstructured":"Wang, T.C., Liu, M.Y., Zhu, J.Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional GANs. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 8798\u20138807 (2018)","DOI":"10.1109\/CVPR.2018.00917"},{"key":"11_CR63","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1007\/978-3-319-46493-0_20","volume-title":"Computer Vision \u2013 ECCV 2016","author":"X Wang","year":"2016","unstructured":"Wang, X., Gupta, A.: Generative image modeling using style and structure adversarial networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 318\u2013335. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_20"},{"key":"11_CR64","doi-asserted-by":"crossref","unstructured":"Xian, W., et al.: TextureGAN: controlling deep image synthesis with texture patches. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 8456\u20138465 (2018)","DOI":"10.1109\/CVPR.2018.00882"},{"key":"11_CR65","doi-asserted-by":"crossref","unstructured":"Xu, Z., Bi, S., Sunkavalli, K., Hadap, S., Su, H., Ramamoorthi, R.: Deep view synthesis from sparse photometric images. ACM Trans. Graph. 38(4) (2019)","DOI":"10.1145\/3306346.3323007"},{"key":"11_CR66","doi-asserted-by":"crossref","unstructured":"Yu, Y., Smith, W.A.: InverseRenderNet: learning single image inverse rendering. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR), pp. 3155\u20133164 (2019)","DOI":"10.1109\/CVPR.2019.00327"},{"key":"11_CR67","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 Computer Vision and Pattern Recognition (CVPR), pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"11_CR68","first-page":"1","volume":"37","author":"T Zhou","year":"2018","unstructured":"Zhou, T., Tucker, R., Flynn, J., Fyffe, G., Snavely, N.: Stereo magnification: learning view synthesis using multiplane images. ACM Trans. Graph. 37, 1\u201312 (2018)","journal-title":"ACM Trans. Graph."},{"key":"11_CR69","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1007\/978-3-319-46493-0_18","volume-title":"Computer Vision \u2013 ECCV 2016","author":"T Zhou","year":"2016","unstructured":"Zhou, T., Tulsiani, S., Sun, W., Malik, J., Efros, A.A.: View synthesis by appearance flow. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 286\u2013301. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_18"},{"key":"11_CR70","doi-asserted-by":"crossref","unstructured":"Zhu, J.Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"},{"key":"11_CR71","unstructured":"Zhu, J.Y., et al.: Toward multimodal image-to-image translation. In: Neural Information Processing Systems, pp. 465\u2013476 (2017)"},{"key":"11_CR72","doi-asserted-by":"crossref","unstructured":"Zitnick, C.L., Kang, S.B., Uyttendaele, M., Winder, S.A.J., Szeliski, R.: High-quality video view interpolation using a layered representation. In: SIGGRAPH 2004 (2004)","DOI":"10.1145\/1186562.1015766"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58452-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:05:53Z","timestamp":1730592353000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58452-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030584511","9783030584528"],"references-count":72,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58452-8_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"3 November 2020","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":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","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":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"27% - 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","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":"7","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)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}