{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T05:45:27Z","timestamp":1742967927133,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319494081"},{"type":"electronic","value":"9783319494098"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-49409-8_56","type":"book-chapter","created":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T05:19:03Z","timestamp":1558329543000},"page":"665-681","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Categorization and Pose Estimation of Sets of Occluded Objects in Cluttered Scenes from Depth Data and Generic Object Models Using Joint Parsing"],"prefix":"10.1007","author":[{"given":"Hector","family":"Basevi","sequence":"first","affiliation":[]},{"given":"Ale\u0161","family":"Leonardis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,11,24]]},"reference":[{"key":"56_CR1","unstructured":"Hejrati, M., Ramanan, D.: Analyzing 3D objects in cluttered images. In: Advances in Neural Information Processing Systems, pp. 593\u2013601 (2012)"},{"key":"56_CR2","doi-asserted-by":"crossref","unstructured":"Lim, J.J., Pirsiavash, H., Torralba, A.: Parsing IKEA objects: fine pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2992\u20132999. IEEE (2013)","DOI":"10.1109\/ICCV.2013.372"},{"key":"56_CR3","doi-asserted-by":"crossref","unstructured":"Yoruk, E., Vidal, R.: Efficient object localization and pose estimation with 3D wireframe models. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 538\u2013545 (2013)","DOI":"10.1109\/ICCVW.2013.127"},{"key":"56_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1007\/978-3-319-10605-2_35","volume-title":"Computer Vision \u2013 ECCV 2014","author":"E Brachmann","year":"2014","unstructured":"Brachmann, E., Krull, A., Michel, F., Gumhold, S., Shotton, J., Rother, C.: Learning 6D object pose estimation using 3D object coordinates. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8690, pp. 536\u2013551. Springer, Heidelberg (2014). doi:\n 10.1007\/978-3-319-10605-2_35"},{"key":"56_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/978-3-319-10584-0_23","volume-title":"Computer Vision \u2013 ECCV 2014","author":"S Gupta","year":"2014","unstructured":"Gupta, S., Girshick, R., Arbel\u00e1ez, P., Malik, J.: Learning rich features from RGB-D images for object detection and segmentation. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8695, pp. 345\u2013360. Springer, Heidelberg (2014). doi:\n 10.1007\/978-3-319-10584-0_23"},{"key":"56_CR6","doi-asserted-by":"crossref","unstructured":"Peng, X., Sun, B., Ali, K., Saenko, K.: Learning deep object detectors from 3D models. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1278\u20131286 (2015)","DOI":"10.1109\/ICCV.2015.151"},{"key":"56_CR7","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"key":"56_CR8","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"56_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1007\/978-3-319-10590-1_54","volume-title":"Computer Vision \u2013 ECCV 2014","author":"N Zhang","year":"2014","unstructured":"Zhang, N., Donahue, J., Girshick, R., Darrell, T.: Part-based R-CNNs for fine-grained category detection. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 834\u2013849. Springer, Heidelberg (2014). doi:\n 10.1007\/978-3-319-10590-1_54"},{"key":"56_CR10","doi-asserted-by":"crossref","unstructured":"Gupta, S., Arbel\u00e1ez, P., Girshick, R., Malik, J.: Aligning 3D models to RGB-D images of cluttered scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4731\u20134740 (2015)","DOI":"10.1109\/CVPR.2015.7299105"},{"key":"56_CR11","doi-asserted-by":"crossref","unstructured":"Song, S., Xiao, J.: Deep sliding shapes for amodal 3D object detection in RGB-D images. CoRR abs\/1511.02300 (2015)","DOI":"10.1109\/CVPR.2016.94"},{"issue":"1","key":"56_CR12","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1145\/2398356.2398381","volume":"56","author":"J Shotton","year":"2013","unstructured":"Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., Moore, R.: Real-time human pose recognition in parts from single depth images. Commun. ACM 56(1), 116\u2013124 (2013)","journal-title":"Commun. ACM"},{"key":"56_CR13","doi-asserted-by":"crossref","unstructured":"Karpathy, A., Toderici, G., Shetty, S., Leung, T., Sukthankar, R., Fei-Fei, L.: Large-scale video classification with convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1725\u20131732 (2014)","DOI":"10.1109\/CVPR.2014.223"},{"issue":"11","key":"56_CR14","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1109\/TPAMI.2015.2408347","volume":"37","author":"B Pepik","year":"2015","unstructured":"Pepik, B., Stark, M., Gehler, P., Schiele, B.: Multi-view and 3D deformable part models. IEEE Trans. Pattern Anal. Mach. Intell. 37(11), 2232\u20132245 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"56_CR15","doi-asserted-by":"publisher","first-page":"2608","DOI":"10.1109\/TPAMI.2013.87","volume":"35","author":"MZ Zia","year":"2013","unstructured":"Zia, M.Z., Stark, M., Schiele, B., Schindler, K.: Detailed 3D representations for object recognition and modeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(11), 2608\u20132623 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"56_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1007\/978-3-642-37331-2_42","volume-title":"Computer Vision \u2013 ACCV 2012","author":"S Hinterstoisser","year":"2013","unstructured":"Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., Navab, N.: Model based training, detection and pose estimation of texture-less 3D objects in heavily cluttered scenes. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012. LNCS, vol. 7724, pp. 548\u2013562. Springer, Heidelberg (2013). doi:\n 10.1007\/978-3-642-37331-2_42"},{"key":"56_CR17","doi-asserted-by":"crossref","unstructured":"Krull, A., Brachmann, E., Michel, F., Ying Yang, M., Gumhold, S., Rother, C.: Learning analysis-by-synthesis for 6D pose estimation in RGB-D images. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 954\u2013962 (2015)","DOI":"10.1109\/ICCV.2015.115"},{"key":"56_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1007\/978-3-319-10599-4_41","volume-title":"Computer Vision \u2013 ECCV 2014","author":"S Song","year":"2014","unstructured":"Song, S., Xiao, J.: Sliding shapes for 3D object detection in depth images. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 634\u2013651. Springer, Heidelberg (2014). doi:\n 10.1007\/978-3-319-10599-4_41"},{"key":"56_CR19","unstructured":"Guo, R., Zou, C., Hoiem, D.: Predicting complete 3D models of indoor scenes. CoRR abs\/1504.02437 (2015)"},{"key":"56_CR20","doi-asserted-by":"crossref","unstructured":"Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the IEEE International Conference on Computer Vision, vol. 2, pp. 1150\u20131157. IEEE (1999)","DOI":"10.1109\/ICCV.1999.790410"},{"key":"56_CR21","doi-asserted-by":"crossref","unstructured":"Martinez, M., Collet, A., Srinivasa, S.S.: Moped: a scalable and low latency object recognition and pose estimation system. In: IEEE International Conference on Robotics and Automation, pp. 2043\u20132049. IEEE (2010)","DOI":"10.1109\/ROBOT.2010.5509801"},{"key":"56_CR22","doi-asserted-by":"crossref","unstructured":"Wohlhart, P., Lepetit, V.: Learning descriptors for object recognition and 3D pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3109\u20133118 (2015)","DOI":"10.1109\/CVPR.2015.7298930"},{"key":"56_CR23","unstructured":"Crivellaro, A., Rad, M., Verdie, Y., Moo Yi, K., Fua, P., Lepetit, V.: A novel representation of parts for accurate 3D object detection and tracking in monocular images. In: Proceedings of the IEEE International Conference on Computer Vision, 4391\u20134399 (2015)"},{"key":"56_CR24","doi-asserted-by":"crossref","unstructured":"Drost, B., Ulrich, M., Navab, N., Ilic, S.: Model globally, match locally: efficient and robust 3D object recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, p. 5 (2010)","DOI":"10.1109\/CVPR.2010.5540108"},{"key":"56_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/978-3-642-33718-5_15","volume-title":"Computer Vision \u2013 ECCV 2012","author":"S Holzer","year":"2012","unstructured":"Holzer, S., Shotton, J., Kohli, P.: Learning to efficiently detect repeatable interest points in depth data. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7572, pp. 200\u2013213. Springer, Heidelberg (2012). doi:\n 10.1007\/978-3-642-33718-5_15"},{"key":"56_CR26","doi-asserted-by":"crossref","unstructured":"Hoda\u0148, T., Zabulis, X., Lourakis, M., Obdr\u017e\u00e1lek, \u0160., Matas, J.: Detection and fine 3D pose estimation of texture-less objects in RGB-D images. In: IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 4421\u20134428. IEEE (2015)","DOI":"10.1109\/IROS.2015.7354005"},{"key":"56_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1007\/978-3-642-15555-0_48","volume-title":"Computer Vision \u2013 ECCV 2010","author":"M Sun","year":"2010","unstructured":"Sun, M., Bradski, G., Xu, B.-X., Savarese, S.: Depth-encoded hough voting for joint object detection and shape recovery. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6315, pp. 658\u2013671. Springer, Heidelberg (2010). doi:\n 10.1007\/978-3-642-15555-0_48"},{"key":"56_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1007\/978-3-319-10599-4_30","volume-title":"Computer Vision \u2013 ECCV 2014","author":"A Tejani","year":"2014","unstructured":"Tejani, A., Tang, D., Kouskouridas, R., Kim, T.-K.: Latent-class hough forests for 3D object detection and pose estimation. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 462\u2013477. Springer, Heidelberg (2014). doi:\n 10.1007\/978-3-319-10599-4_30"},{"key":"56_CR29","doi-asserted-by":"crossref","unstructured":"Doumanoglou, A., Kouskouridas, R., Malassiotis, S., Kim, T.K.: Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd. ArXiv e-prints, December 2015","DOI":"10.1109\/CVPR.2016.390"},{"issue":"2","key":"56_CR30","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/s11263-014-0795-4","volume":"112","author":"B Zheng","year":"2015","unstructured":"Zheng, B., Zhao, Y., Yu, J., Ikeuchi, K., Zhu, S.C.: Scene understanding by reasoning stability and safety. Int. J. Comput. Vis. 112(2), 221\u2013238 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"56_CR31","doi-asserted-by":"crossref","unstructured":"Jia, Z., Gallagher, A., Saxena, A., Chen, T.: 3D-based reasoning with blocks, support, and stability. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2013)","DOI":"10.1109\/CVPR.2013.8"},{"issue":"1","key":"56_CR32","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1109\/72.265956","volume":"5","author":"DB Fogel","year":"1994","unstructured":"Fogel, D.B.: An introduction to simulated evolutionary optimization. IEEE Trans. Neural Netw. 5(1), 3\u201314 (1994)","journal-title":"IEEE Trans. Neural Netw."},{"key":"56_CR33","unstructured":"Walas, K., Leonardis, A.: UoB highly occluded object challenge (UoB-HOOC). \n http:\/\/www.cs.bham.ac.uk\/research\/projects\/uob-hooc\/\n \n . Accessed 11 Mar 2016"},{"key":"56_CR34","unstructured":"Bouguet, J.Y.: Camera calibration toolbox for matlab (2004)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2016 Workshops"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-49409-8_56","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,10]],"date-time":"2020-10-10T01:33:17Z","timestamp":1602293597000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-49409-8_56"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319494081","9783319494098"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-49409-8_56","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"24 November 2016","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":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.eccv2016.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"}]}}