{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T05:40:10Z","timestamp":1773294010724,"version":"3.50.1"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030110178","type":"print"},{"value":"9783030110185","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-11018-5_6","type":"book-chapter","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T05:50:50Z","timestamp":1548309050000},"page":"64-77","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["3D Human Body Reconstruction from a Single Image via Volumetric Regression"],"prefix":"10.1007","author":[{"given":"Aaron S.","family":"Jackson","sequence":"first","affiliation":[]},{"given":"Chris","family":"Manafas","sequence":"additional","affiliation":[]},{"given":"Georgios","family":"Tzimiropoulos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,23]]},"reference":[{"key":"6_CR1","doi-asserted-by":"crossref","unstructured":"Jackson, A.S., Bulat, A., Argyriou, V., Tzimiropoulos, G.: Large pose 3D face reconstruction from a single image via direct volumetric CNN regression. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 1031\u20131039. IEEE (2017)","DOI":"10.1109\/ICCV.2017.117"},{"key":"6_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/978-3-319-46454-1_34","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Bogo","year":"2016","unstructured":"Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M.J.: Keep It SMPL: automatic estimation of 3D human pose and shape from a single image. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016, Part V. LNCS, vol. 9909, pp. 561\u2013578. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46454-1_34"},{"key":"6_CR3","doi-asserted-by":"crossref","unstructured":"Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. In: ACM SIGGRAPH Computer Graphics, vol. 21, pp. 163\u2013169. ACM (1987)","DOI":"10.1145\/37402.37422"},{"key":"6_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1007\/978-3-319-16808-1_23","volume-title":"Computer Vision \u2013 ACCV 2014","author":"S Li","year":"2015","unstructured":"Li, S., Chan, A.B.: 3D human pose estimation from monocular images with deep convolutional neural network. In: Cremers, D., Reid, I., Saito, H., Yang, M.-H. (eds.) ACCV 2014. LNCS, vol. 9004, pp. 332\u2013347. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16808-1_23"},{"key":"6_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1007\/978-3-319-49409-8_15","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"S Park","year":"2016","unstructured":"Park, S., Hwang, J., Kwak, N.: 3D human pose estimation using convolutional neural networks with 2D pose information. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016, Part III. LNCS, vol. 9915, pp. 156\u2013169. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49409-8_15"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Tekin, B., Katircioglu, I., Salzmann, M., Lepetit, V., Fua, P.: Structured prediction of 3D human pose with deep neural networks. arXiv preprint arXiv:1605.05180 (2016)","DOI":"10.5244\/C.30.130"},{"key":"6_CR7","doi-asserted-by":"crossref","unstructured":"Tekin, B., Rozantsev, A., Lepetit, V., Fua, P.: Direct prediction of 3D body poses from motion compensated sequences. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 991\u20131000 (2016)","DOI":"10.1109\/CVPR.2016.113"},{"key":"6_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1007\/978-3-319-49409-8_17","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"X Zhou","year":"2016","unstructured":"Zhou, X., Sun, X., Zhang, W., Liang, S., Wei, Y.: Deep kinematic pose regression. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016, Part III. LNCS, vol. 9915, pp. 186\u2013201. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49409-8_17"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Chen, W., et al.: Synthesizing training images for boosting human 3D pose estimation. In: 2016 Fourth International Conference on 3D Vision (3DV), pp. 479\u2013488. IEEE (2016)","DOI":"10.1109\/3DV.2016.58"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Ghezelghieh, M.F., Kasturi, R., Sarkar, S.: Learning camera viewpoint using CNN to improve 3D body pose estimation. In: 2016 Fourth International Conference on 3D Vision (3DV), pp. 685\u2013693. IEEE (2016)","DOI":"10.1109\/3DV.2016.75"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Zhou, X., Zhu, M., Leonardos, S., Derpanis, K.G., Daniilidis, K.: Sparseness meets deepness: 3D human pose estimation from monocular video. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4966\u20134975 (2016)","DOI":"10.1109\/CVPR.2016.537"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Pavlakos, G., Zhou, X., Derpanis, K.G., Daniilidis, K.: Coarse-to-fine volumetric prediction for single-image 3D human pose. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1263\u20131272. IEEE (2017)","DOI":"10.1109\/CVPR.2017.139"},{"issue":"4","key":"6_CR13","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1145\/3072959.3073596","volume":"36","author":"D Mehta","year":"2017","unstructured":"Mehta, D.: Vnect: Real-time 3D human pose estimation with a single RGB camera. ACM Trans. Graph. (TOG) 36(4), 44 (2017)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"6_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/978-3-319-46478-7_44","volume-title":"Computer Vision \u2013 ECCV 2016","author":"A Bulat","year":"2016","unstructured":"Bulat, A., Tzimiropoulos, G.: Human pose estimation via convolutional part heatmap regression. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016, Part VII. LNCS, vol. 9911, pp. 717\u2013732. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46478-7_44"},{"key":"6_CR15","doi-asserted-by":"crossref","unstructured":"Balan, A.O., Sigal, L., Black, M.J., Davis, J.E., Haussecker, H.W.: Detailed human shape and pose from images. In: 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2007)","DOI":"10.1109\/CVPR.2007.383340"},{"key":"6_CR16","unstructured":"Grest, D., Herzog, D., Koch, R.: Human model fitting from monocular posture images"},{"key":"6_CR17","unstructured":"Guan, P., Weiss, A., Balan, A.O., Black, M.J.: Estimating human shape and pose from a single image. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 1381\u20131388. IEEE (2009)"},{"issue":"3","key":"6_CR18","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1145\/1073204.1073207","volume":"24","author":"Dragomir Anguelov","year":"2005","unstructured":"Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., Davis, J.: Scape: shape completion and animation of people. In: ACM Transactions on Graphics (TOG), vol. 24, pp. 408\u2013416. ACM (2005)","journal-title":"ACM Transactions on Graphics"},{"key":"6_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1007\/978-3-642-15558-1_22","volume-title":"Computer Vision \u2013 ECCV 2010","author":"Y Chen","year":"2010","unstructured":"Chen, Y., Kim, T.-K., Cipolla, R.: Inferring 3D shapes and deformations from single views. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part III. LNCS, vol. 6313, pp. 300\u2013313. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15558-1_22"},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Jiang, H.: 3D human pose reconstruction using millions of exemplars. In: 2010 20th International Conference on Pattern Recognition (ICPR), pp. 1674\u20131677. IEEE (2010)","DOI":"10.1109\/ICPR.2010.414"},{"key":"6_CR21","doi-asserted-by":"crossref","unstructured":"Zanfir, A., Marinoiu, E., Sminchisescu, C.: Monocular 3D pose and shape estimation of multiple people in natural scenes - the importance of multiple scene constraints. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2018","DOI":"10.1109\/CVPR.2018.00229"},{"key":"6_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1007\/978-3-642-33765-9_41","volume-title":"Computer Vision \u2013 ECCV 2012","author":"V Ramakrishna","year":"2012","unstructured":"Ramakrishna, V., Kanade, T., Sheikh, Y.: Reconstructing 3D human pose from 2D image landmarks. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part IV. LNCS, vol. 7575, pp. 573\u2013586. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33765-9_41"},{"issue":"6","key":"6_CR23","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1145\/2816795.2818013","volume":"34","author":"M Loper","year":"2015","unstructured":"Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: SMPL: a skinned multi-person linear model. ACM Trans. Graph. 34(6), 248 (2015)","journal-title":"ACM Trans. Graph."},{"key":"6_CR24","doi-asserted-by":"crossref","unstructured":"Varol, G., et al.: Learning from synthetic humans. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), pp. 4627\u20134635. IEEE (2017)","DOI":"10.1109\/CVPR.2017.492"},{"issue":"4","key":"6_CR25","doi-asserted-by":"publisher","first-page":"120:1","DOI":"10.1145\/2766993","volume":"34","author":"G Pons-Moll","year":"2015","unstructured":"Pons-Moll, G., Romero, J., Mahmood, N., Black, M.J.: Dyna: a model of dynamic human shape in motion. ACM Trans. Graph. 34(4), 120:1\u2013120:14 (2015)","journal-title":"ACM Trans. Graph."},{"key":"6_CR26","doi-asserted-by":"crossref","unstructured":"Joo, H., Simon, T., Sheikh, Y.: Total capture: a 3D deformation model for tracking faces, hands, and bodies. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2018","DOI":"10.1109\/CVPR.2018.00868"},{"key":"6_CR27","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"6_CR28","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"6_CR29","doi-asserted-by":"crossref","unstructured":"Ionescu, C., Li, F., Sminchisescu, C.: Latent structured models for human pose estimation. In: International Conference on Computer Vision (2011)","DOI":"10.1109\/ICCV.2011.6126500"},{"issue":"7","key":"6_CR30","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2014","unstructured":"Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3.6m: large scale datasets and predictive methods for 3D human sensing in natural environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1325\u20131339 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"6_CR31","unstructured":"Hinton, G., Srivastava, N., Swersky, K.: Neural networks for machine learning lecture 6a overview of mini-batch gradient descent"},{"key":"6_CR32","doi-asserted-by":"crossref","unstructured":"Bulat, A., Tzimiropoulos, G.: Binarized convolutional landmark localizers for human pose estimation and face alignment with limited resources. In: International Conference on Computer Vision (2017)","DOI":"10.1109\/ICCV.2017.400"},{"key":"6_CR33","unstructured":"Sigal, L., Balan, A., Black, M.J.: Combined discriminative and generative articulated pose and non-rigid shape estimation. In: Advances in Neural Information Processing Systems, pp. 1337\u20131344 (2008)"},{"key":"6_CR34","doi-asserted-by":"crossref","unstructured":"Qiu, Z., Yao, T., Mei, T.: Learning spatio-temporal representation with pseudo-3D residual networks. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 5534\u20135542. IEEE (2017)","DOI":"10.1109\/ICCV.2017.590"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-11018-5_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T01:16:13Z","timestamp":1674350173000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-11018-5_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030110178","9783030110185"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-11018-5_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 January 2019","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":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}