Changes
On December 2, 2024 at 5:38:57 PM UTC,
admin:
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Added resource Original Metadata to ModelNet40
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| 68 | "doi": "10.57702/uexf99xg", | 68 | "doi": "10.57702/uexf99xg", | ||
| 69 | "doi_date_published": "2024-11-25", | 69 | "doi_date_published": "2024-11-25", | ||
| 70 | "doi_publisher": "TIB", | 70 | "doi_publisher": "TIB", | ||
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| 73 | "extra_authors": [ | 73 | "extra_authors": [ | ||
| 74 | { | 74 | { | ||
| 75 | "extra_author": "Shuran Song", | 75 | "extra_author": "Shuran Song", | ||
| 76 | "orcid": "" | 76 | "orcid": "" | ||
| 77 | }, | 77 | }, | ||
| 78 | { | 78 | { | ||
| 79 | "extra_author": "Aditya Khosla", | 79 | "extra_author": "Aditya Khosla", | ||
| 80 | "orcid": "" | 80 | "orcid": "" | ||
| 81 | }, | 81 | }, | ||
| 82 | { | 82 | { | ||
| 83 | "extra_author": "Fisher Yu", | 83 | "extra_author": "Fisher Yu", | ||
| 84 | "orcid": "" | 84 | "orcid": "" | ||
| 85 | }, | 85 | }, | ||
| 86 | { | 86 | { | ||
| 87 | "extra_author": "Linguang Zhang", | 87 | "extra_author": "Linguang Zhang", | ||
| 88 | "orcid": "" | 88 | "orcid": "" | ||
| 89 | }, | 89 | }, | ||
| 90 | { | 90 | { | ||
| 91 | "extra_author": "Xiaoou Tang", | 91 | "extra_author": "Xiaoou Tang", | ||
| 92 | "orcid": "" | 92 | "orcid": "" | ||
| 93 | }, | 93 | }, | ||
| 94 | { | 94 | { | ||
| 95 | "extra_author": "Jianxiong Xiao", | 95 | "extra_author": "Jianxiong Xiao", | ||
| 96 | "orcid": "" | 96 | "orcid": "" | ||
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| 250 | "title": "3D object understanding" | 250 | "title": "3D object understanding" | ||
| 251 | }, | 251 | }, | ||
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| 254 | "display_name": "CAD Models", | 254 | "display_name": "CAD Models", | ||
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| 257 | "name": "cad-models", | 257 | "name": "cad-models", | ||
| 258 | "title": "CAD Models" | 258 | "title": "CAD Models" | ||
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| 282 | "title": "Mesh Registration" | 282 | "title": "Mesh Registration" | ||
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| 298 | "title": "Object Recognition" | 298 | "title": "Object Recognition" | ||
| 299 | }, | 299 | }, | ||
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| 306 | "title": "Point Cloud Classification" | 306 | "title": "Point Cloud Classification" | ||
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| 314 | "title": "Point Cloud Registration" | 314 | "title": "Point Cloud Registration" | ||
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| 330 | "title": "Pose Estimation" | 330 | "title": "Pose Estimation" | ||
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| 338 | "title": "Semantic Segmentation" | 338 | "title": "Semantic Segmentation" | ||
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| 346 | "title": "Shape Classification" | 346 | "title": "Shape Classification" | ||
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| 362 | "title": "Shape segmentation" | 362 | "title": "Shape segmentation" | ||
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| 367 | "landing_page": "https://www.cs.unc.edu/~eht/Research/ModelNet40/", | 367 | "landing_page": "https://www.cs.unc.edu/~eht/Research/ModelNet40/", | ||
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| 373 | "notes": "Point cloud registration is a crucial problem in computer | 373 | "notes": "Point cloud registration is a crucial problem in computer | ||
| 374 | vision and robotics. Existing methods either rely on matching local | 374 | vision and robotics. Existing methods either rely on matching local | ||
| 375 | geometric features, which are sensitive to the pose differences, or | 375 | geometric features, which are sensitive to the pose differences, or | ||
| 376 | leverage global shapes, which leads to inconsistency when facing | 376 | leverage global shapes, which leads to inconsistency when facing | ||
| 377 | distribution variances such as partial overlapping.", | 377 | distribution variances such as partial overlapping.", | ||
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| 447 | "vocabulary_id": null | 488 | "vocabulary_id": null | ||
| 448 | }, | 489 | }, | ||
| 449 | { | 490 | { | ||
| 450 | "display_name": "3D Point Cloud", | 491 | "display_name": "3D Point Cloud", | ||
| 451 | "id": "af068727-d74f-4569-ae98-7f924b04c4bd", | 492 | "id": "af068727-d74f-4569-ae98-7f924b04c4bd", | ||
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| 455 | }, | 496 | }, | ||
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| 462 | }, | 503 | }, | ||
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| 468 | "vocabulary_id": null | 509 | "vocabulary_id": null | ||
| 469 | }, | 510 | }, | ||
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| 471 | "display_name": "3D Shape Classification", | 512 | "display_name": "3D Shape Classification", | ||
| 472 | "id": "b8a3e7c5-5c91-49eb-85b1-e0d45cc5c61d", | 513 | "id": "b8a3e7c5-5c91-49eb-85b1-e0d45cc5c61d", | ||
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| 475 | "vocabulary_id": null | 516 | "vocabulary_id": null | ||
| 476 | }, | 517 | }, | ||
| 477 | { | 518 | { | ||
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| 482 | "vocabulary_id": null | 523 | "vocabulary_id": null | ||
| 483 | }, | 524 | }, | ||
| 484 | { | 525 | { | ||
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| 511 | }, | 552 | }, | ||
| 512 | { | 553 | { | ||
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| 757 | { | 798 | { | ||
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| 764 | { | 805 | { | ||
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| 767 | "name": "mesh registration", | 808 | "name": "mesh registration", | ||
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| 778 | { | 819 | { | ||
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| 783 | "vocabulary_id": null | 824 | "vocabulary_id": null | ||
| 784 | }, | 825 | }, | ||
| 785 | { | 826 | { | ||
| 786 | "display_name": "object understanding", | 827 | "display_name": "object understanding", | ||
| 787 | "id": "99287eae-5e22-4fa3-a34e-bf33515de007", | 828 | "id": "99287eae-5e22-4fa3-a34e-bf33515de007", | ||
| 788 | "name": "object understanding", | 829 | "name": "object understanding", | ||
| 789 | "state": "active", | 830 | "state": "active", | ||
| 790 | "vocabulary_id": null | 831 | "vocabulary_id": null | ||
| 791 | }, | 832 | }, | ||
| 792 | { | 833 | { | ||
| 793 | "display_name": "point cloud", | 834 | "display_name": "point cloud", | ||
| 794 | "id": "fcb968fe-38b8-4b04-a049-e69bcf7b9f19", | 835 | "id": "fcb968fe-38b8-4b04-a049-e69bcf7b9f19", | ||
| 795 | "name": "point cloud", | 836 | "name": "point cloud", | ||
| 796 | "state": "active", | 837 | "state": "active", | ||
| 797 | "vocabulary_id": null | 838 | "vocabulary_id": null | ||
| 798 | }, | 839 | }, | ||
| 799 | { | 840 | { | ||
| 800 | "display_name": "point clouds", | 841 | "display_name": "point clouds", | ||
| 801 | "id": "c904c4ed-90b6-4e26-99e0-5201bce31b75", | 842 | "id": "c904c4ed-90b6-4e26-99e0-5201bce31b75", | ||
| 802 | "name": "point clouds", | 843 | "name": "point clouds", | ||
| 803 | "state": "active", | 844 | "state": "active", | ||
| 804 | "vocabulary_id": null | 845 | "vocabulary_id": null | ||
| 805 | }, | 846 | }, | ||
| 806 | { | 847 | { | ||
| 807 | "display_name": "segmentation", | 848 | "display_name": "segmentation", | ||
| 808 | "id": "7ce0e509-9f57-44c4-a015-f1ab9872bb44", | 849 | "id": "7ce0e509-9f57-44c4-a015-f1ab9872bb44", | ||
| 809 | "name": "segmentation", | 850 | "name": "segmentation", | ||
| 810 | "state": "active", | 851 | "state": "active", | ||
| 811 | "vocabulary_id": null | 852 | "vocabulary_id": null | ||
| 812 | }, | 853 | }, | ||
| 813 | { | 854 | { | ||
| 814 | "display_name": "shape classification", | 855 | "display_name": "shape classification", | ||
| 815 | "id": "5e942fb6-8cd1-4fec-bd47-85b57a5bea9c", | 856 | "id": "5e942fb6-8cd1-4fec-bd47-85b57a5bea9c", | ||
| 816 | "name": "shape classification", | 857 | "name": "shape classification", | ||
| 817 | "state": "active", | 858 | "state": "active", | ||
| 818 | "vocabulary_id": null | 859 | "vocabulary_id": null | ||
| 819 | }, | 860 | }, | ||
| 820 | { | 861 | { | ||
| 821 | "display_name": "shape recognition", | 862 | "display_name": "shape recognition", | ||
| 822 | "id": "7a5d3e66-4990-4fba-9d63-bfeda9defa76", | 863 | "id": "7a5d3e66-4990-4fba-9d63-bfeda9defa76", | ||
| 823 | "name": "shape recognition", | 864 | "name": "shape recognition", | ||
| 824 | "state": "active", | 865 | "state": "active", | ||
| 825 | "vocabulary_id": null | 866 | "vocabulary_id": null | ||
| 826 | }, | 867 | }, | ||
| 827 | { | 868 | { | ||
| 828 | "display_name": "shape retrieval", | 869 | "display_name": "shape retrieval", | ||
| 829 | "id": "ea3c7cb7-ab35-4560-adda-95e01c6e0358", | 870 | "id": "ea3c7cb7-ab35-4560-adda-95e01c6e0358", | ||
| 830 | "name": "shape retrieval", | 871 | "name": "shape retrieval", | ||
| 831 | "state": "active", | 872 | "state": "active", | ||
| 832 | "vocabulary_id": null | 873 | "vocabulary_id": null | ||
| 833 | }, | 874 | }, | ||
| 834 | { | 875 | { | ||
| 835 | "display_name": "shape segmentation", | 876 | "display_name": "shape segmentation", | ||
| 836 | "id": "3cd2cc59-042e-4933-bd70-530340eab16b", | 877 | "id": "3cd2cc59-042e-4933-bd70-530340eab16b", | ||
| 837 | "name": "shape segmentation", | 878 | "name": "shape segmentation", | ||
| 838 | "state": "active", | 879 | "state": "active", | ||
| 839 | "vocabulary_id": null | 880 | "vocabulary_id": null | ||
| 840 | }, | 881 | }, | ||
| 841 | { | 882 | { | ||
| 842 | "display_name": "synthetic dataset", | 883 | "display_name": "synthetic dataset", | ||
| 843 | "id": "81a8d3d6-fe87-4f43-9fde-738b923d6290", | 884 | "id": "81a8d3d6-fe87-4f43-9fde-738b923d6290", | ||
| 844 | "name": "synthetic dataset", | 885 | "name": "synthetic dataset", | ||
| 845 | "state": "active", | 886 | "state": "active", | ||
| 846 | "vocabulary_id": null | 887 | "vocabulary_id": null | ||
| 847 | } | 888 | } | ||
| 848 | ], | 889 | ], | ||
| 849 | "title": "ModelNet40", | 890 | "title": "ModelNet40", | ||
| 850 | "type": "dataset", | 891 | "type": "dataset", | ||
| 851 | "version": "" | 892 | "version": "" | ||
| 852 | } | 893 | } |