{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T12:22:37Z","timestamp":1743078157574,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030954581"},{"type":"electronic","value":"9783030954598"}],"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\/978-3-030-95459-8_23","type":"book-chapter","created":{"date-parts":[[2022,2,17]],"date-time":"2022-02-17T19:02:27Z","timestamp":1645124547000},"page":"376-392","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Inferring Occluded Geometry Improves Performance When Retrieving an\u00a0Object from\u00a0Dense Clutter"],"prefix":"10.1007","author":[{"given":"Andrew","family":"Price","sequence":"first","affiliation":[]},{"given":"Linyi","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Dmitry","family":"Berenson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,17]]},"reference":[{"key":"23_CR1","doi-asserted-by":"crossref","unstructured":"Jonschkowski, R., Eppner, C., H\u00f6fer, S., Mart\u00edn-Mart\u00edn, R., Brock, O.: Probabilistic multiclass segmentation for the Amazon Picking Challenge. In: IROS, pp. 1\u20137. IEEE (2016)","DOI":"10.1109\/IROS.2016.7758087"},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"Schwarz, M., et al.: NimbRo picking: versatile part handling for warehouse automation. In: ICRA, pp. 3032\u20133039. IEEE (2017)","DOI":"10.1109\/ICRA.2017.7989348"},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Milan, A., et al.: Semantic segmentation from limited training data. In: ICRA, pp. 1908\u20131915. IEEE (2018)","DOI":"10.1109\/ICRA.2018.8461082"},{"key":"23_CR4","doi-asserted-by":"crossref","unstructured":"Varley, J., DeChant, C., Richardson, A., Ruales, J., Allen, P.: Shape completion enabled robotic grasping. In: IROS, pp. 2442\u20132447. IEEE (2017)","DOI":"10.1109\/IROS.2017.8206060"},{"key":"23_CR5","doi-asserted-by":"crossref","unstructured":"Yang, B., Wen, H., Wang, S., Clark, R., Markham, A., Trigoni, N.: 3D object reconstruction from a single depth view with adversarial learning. In: ICCV Workshop (2017)","DOI":"10.1109\/ICCVW.2017.86"},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Stilman, M., Schamburek, J.U., Kuffner, J., Asfour, T.: Manipulation planning among movable obstacles. In: ICRA, pp. 3327\u20133332 (2007)","DOI":"10.1109\/ROBOT.2007.363986"},{"issue":"3","key":"23_CR7","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s10514-012-9306-z","volume":"33","author":"MR Dogar","year":"2012","unstructured":"Dogar, M.R., Srinivasa, S.S.: A planning framework for non-prehensile manipulation under clutter and uncertainty. Auton. Robots 33(3), 217\u2013236 (2012). https:\/\/doi.org\/10.1007\/s10514-012-9306-z","journal-title":"Auton. Robots"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Wong, L.L., Kaelbling, L.P., Lozano-Perez, T.: Manipulation-based active search for occluded objects. In: ICRA, pp. 2814\u20132819 (2013)","DOI":"10.1109\/ICRA.2013.6630966"},{"issue":"1\u20132","key":"23_CR9","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/s10514-013-9372-x","volume":"36","author":"MR Dogar","year":"2014","unstructured":"Dogar, M.R., Koval, M.C., Tallavajhula, A., Srinivasa, S.S.: Object search by manipulation. Auton. Robots 36(1\u20132), 153\u2013167 (2014). https:\/\/doi.org\/10.1007\/s10514-013-9372-x","journal-title":"Auton. Robots"},{"key":"23_CR10","doi-asserted-by":"crossref","unstructured":"Li, J.K., Hsu, D., Lee, W.S.: Act to see and see to act: POMDP planning for objects search in clutter. In: IROS, pp. 5701\u20135707, November 2016","DOI":"10.1109\/IROS.2016.7759839"},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Zeng, A., et al.: Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching. In: ICRA (2018)","DOI":"10.1109\/ICRA.2018.8461044"},{"issue":"8","key":"23_CR12","first-page":"951","volume":"31","author":"MY Liu","year":"2012","unstructured":"Liu, M.Y., Tuzel, O., Veeraraghavan, A., Taguchi, Y., Marks, T.K., Chellappa, R.: Fast object localization and pose estimation in heavy clutter for robotic bin picking. IJRR 31(8), 951\u2013973 (2012)","journal-title":"IJRR"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Choi, C., Christensen, H.I.: 3D pose estimation of daily objects using an RGB-D camera. In: IROS (2012)","DOI":"10.1109\/IROS.2012.6386067"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Tulsiani, S., Gupta, S., Fouhey, D., Efros, A.A., Malik, J.: Factoring shape, pose, and layout from the 2D image of a 3D scene. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00039"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Xiang, Y., Schmidt, T., Narayanan, V., Fox, D.: PoseCNN: a convolutional neural network for 6D object pose estimation in cluttered scenes. In: Robotics: Science and Systems (RSS) (2018)","DOI":"10.15607\/RSS.2018.XIV.019"},{"key":"23_CR16","unstructured":"Wu, Z., et al.: 3D ShapeNets: a deep representation for volumetric shapes. In: CVPR, pp. 1912\u20131920 (2015)"},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Firman, M., Mac Aodha, O., Julier, S., Brostow, G.J.: Structured prediction of unobserved voxels from a single depth image. In: CVPR, pp. 5431\u20135440 (2016)","DOI":"10.1109\/CVPR.2016.586"},{"key":"23_CR18","doi-asserted-by":"crossref","unstructured":"Song, S., Yu, F., Zeng, A., Chang, A.X., Savva, M., Funkhouser, T.: Semantic scene completion from a single depth image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1746\u20131754 (2017)","DOI":"10.1109\/CVPR.2017.28"},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"Fan, H., Su, H., Guibas, L.J.: A point set generation network for 3D object reconstruction from a single image. In: CVPR, vol. 2, p. 6 (2017)","DOI":"10.1109\/CVPR.2017.264"},{"issue":"12","key":"23_CR20","doi-asserted-by":"publisher","first-page":"2820","DOI":"10.1109\/TPAMI.2018.2868195","volume":"41","author":"B Yang","year":"2018","unstructured":"Yang, B., Rosa, S., Markham, A., Trigoni, N., Wen, H.: Dense 3D object reconstruction from a single depth view. TPAMI 41(12), 2820\u20132834 (2018)","journal-title":"TPAMI"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: ICCV, pp. 2980\u20132988. IEEE (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"23_CR22","doi-asserted-by":"crossref","unstructured":"Lin, G., Milan, A., Shen, C., Reid, I.: RefineNet: multi-path refinement networks for high-resolution semantic segmentation. In: CVPR, July 2017","DOI":"10.1109\/CVPR.2017.549"},{"key":"23_CR23","doi-asserted-by":"crossref","unstructured":"Pham, T., Do, T.-T., S\u00fcnderhauf, N., Reid, I.: SceneCut: joint geometric and object segmentation for indoor scenes. In: ICRA (2018)","DOI":"10.1109\/ICRA.2018.8461108"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Arbelaez, P.: Boundary extraction in natural images using ultrametric contour maps. In: CVPR Workshop, pp. 182\u2013182. IEEE (2006)","DOI":"10.1109\/CVPRW.2006.48"},{"issue":"4","key":"23_CR25","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1109\/TPAMI.2017.2700300","volume":"40","author":"K Maninis","year":"2017","unstructured":"Maninis, K., Pont-Tuset, J., Arbel\u00e1ez, P., Van Gool, L.: Convolutional oriented boundaries: from image segmentation to high-level tasks. TPAMI 40(4), 819\u2013833 (2017)","journal-title":"TPAMI"},{"key":"23_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1007\/978-3-642-33715-4_54","volume-title":"Computer Vision \u2013 ECCV 2012","author":"N Silberman","year":"2012","unstructured":"Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and support inference from RGBD images. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7576, pp. 746\u2013760. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33715-4_54"},{"issue":"3","key":"23_CR27","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/s10514-012-9321-0","volume":"34","author":"A Hornung","year":"2013","unstructured":"Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robots 34(3), 189\u2013206 (2013). https:\/\/doi.org\/10.1007\/s10514-012-9321-0","journal-title":"Auton. Robots"},{"key":"23_CR28","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"23_CR29","doi-asserted-by":"crossref","unstructured":"Calli, B., Singh, A., Walsman, A., Srinivasa, S., Abbeel, P., Dollar, A.M.: The YCB object and model set: towards common benchmarks for manipulation research. In: ICAR, pp. 510\u2013517. IEEE (2015)","DOI":"10.1109\/ICAR.2015.7251504"},{"key":"23_CR30","doi-asserted-by":"crossref","unstructured":"Kappler, D., Bohg, J., Schaal, S.: Leveraging big data for grasp planning. In: ICRA, pp. 4304\u20134311. IEEE (2015)","DOI":"10.1109\/ICRA.2015.7139793"},{"key":"23_CR31","unstructured":"Chang, A.X., et al.: ShapeNet: an information-rich 3D model repository (2015). arXiv:1512.03012"},{"key":"23_CR32","unstructured":"Min, P.: Binvox (2004). http:\/\/www.patrickmin.com\/binvox. Accessed 01 May 2018"},{"issue":"2","key":"23_CR33","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1109\/TASE.2014.2361346","volume":"12","author":"M Gupta","year":"2015","unstructured":"Gupta, M., M\u00fcller, J., Sukhatme, G.S.: Using manipulation primitives for object sorting in cluttered environments. IEEE Trans. Autom. Sci. Eng. 12(2), 608\u2013614 (2015)","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"23_CR34","doi-asserted-by":"crossref","unstructured":"Boularias, A., Bagnell, J.A., Stentz, A.: Learning to manipulate unknown objects in clutter by reinforcement. In: AAAI, January 2015","DOI":"10.1609\/aaai.v29i1.9378"}],"container-title":["Springer Proceedings in Advanced Robotics","Robotics Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-95459-8_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T20:57:05Z","timestamp":1726693025000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-95459-8_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030954581","9783030954598"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-95459-8_23","relation":{},"ISSN":["2511-1256","2511-1264"],"issn-type":[{"type":"print","value":"2511-1256"},{"type":"electronic","value":"2511-1264"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"17 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISRR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The International Symposium of Robotics Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hanoi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isrr2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/h2t-projects.webarchiv.kit.edu\/Projects\/ISRR2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}