Changes

On December 3, 2024 at 12:01:33 AM UTC, admin:
Changed title to NYU-Depth V2 (previously NYU Depth v2)
Set author of NYU-Depth V2 to Seungyeop Lee (previously P. K. Nathan Silberman)
Updated description of NYU-Depth V2 from
The NYU Depth v2 dataset contains both RGB images and depth maps taken by Microsoft Kinect from 464 different indoor scenes at resolution of 640x480.
to
The NYU-Depth V2 dataset contains pairs of RGB and depth images collected from Microsoft Kinect in 464 indoor scenes.
Removed the following tags from NYU-Depth V2
Added the following tags to NYU-Depth V2
Changed value of field defined_in to https://doi.org/10.48550/arXiv.2203.10856 in NYU-Depth V2
Changed value of field extra_authors to [{'extra_author': 'Knut Peterson', 'orcid': ''}, {'extra_author': 'Solmaz Arezoomandan', 'orcid': ''}, {'extra_author': 'Bill Cai', 'orcid': ''}, {'extra_author': 'Peihan Li', 'orcid': ''}, {'extra_author': 'Lifeng Zhou', 'orcid': ''}, {'extra_author': 'David Han', 'orcid': ''}] in NYU-Depth V2
Changed value of field citation to ['https://doi.org/10.48550/arXiv.2309.01624'] in NYU-Depth V2
Changed value of field landing_page to https://www.cs.nyu.edu/~ylclab/research/datasets/nyu_depth_v2.html in NYU-Depth V2
Deleted resource Original Metadata from NYU-Depth V2
              
    
          
          
        
        
            f 1 { f 1 {
            2   "access_rights": "", 2   "access_rights": "",
            n 3   "author": "P. K. Nathan Silberman", n 3   "author": "Seungyeop Lee",
            4   "author_email": "", 4   "author_email": "",
            n 5   "citation": [], n 5   "citation": [
            6     "https://doi.org/10.48550/arXiv.2309.01624"
            7   ],
            6   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", 8   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            n 7   "defined_in": "", n 9   "defined_in": "https://doi.org/10.48550/arXiv.2203.10856",
            8   "doi": "10.57702/wjfr6tqu", 10   "doi": "10.57702/wjfr6tqu",
            9   "doi_date_published": "2024-12-02", 11   "doi_date_published": "2024-12-02",
            10   "doi_publisher": "TIB", 12   "doi_publisher": "TIB",
            11   "doi_status": true, 13   "doi_status": true,
            12   "domain": "https://service.tib.eu/ldmservice", 14   "domain": "https://service.tib.eu/ldmservice",
            13   "extra_authors": [ 15   "extra_authors": [
            14     { 16     {
            n 15       "extra_author": "Derek Hoiem", n 17       "extra_author": "Knut Peterson",
            16       "orcid": "" 18       "orcid": ""
            17     }, 19     },
            18     { 20     {
            n n 21       "extra_author": "Solmaz Arezoomandan",
            22       "orcid": ""
            23     },
            24     {
            25       "extra_author": "Bill Cai",
            26       "orcid": ""
            27     },
            28     {
            29       "extra_author": "Peihan Li",
            30       "orcid": ""
            31     },
            32     {
            19       "extra_author": "R. Fergus", 33       "extra_author": "Lifeng Zhou",
            34       "orcid": ""
            35     },
            36     {
            37       "extra_author": "David Han",
            20       "orcid": "" 38       "orcid": ""
            21     } 39     }
            22   ], 40   ],
            23   "groups": [ 41   "groups": [
            n n 42     {
            43       "description": "",
            44       "display_name": "Benchmark",
            45       "id": "e3c09ae3-950f-4070-b72e-01b7846cae0f",
            46       "image_display_url": "",
            47       "name": "benchmark",
            48       "title": "Benchmark"
            49     },
            24     { 50     {
            25       "description": "", 51       "description": "",
            26       "display_name": "Computer Vision", 52       "display_name": "Computer Vision",
            27       "id": "d09caf7c-26c7-4e4d-bb8e-49476a90ba25", 53       "id": "d09caf7c-26c7-4e4d-bb8e-49476a90ba25",
            28       "image_display_url": "", 54       "image_display_url": "",
            29       "name": "computer-vision", 55       "name": "computer-vision",
            30       "title": "Computer Vision" 56       "title": "Computer Vision"
            31     }, 57     },
            32     { 58     {
            33       "description": "", 59       "description": "",
            34       "display_name": "Depth Estimation", 60       "display_name": "Depth Estimation",
            35       "id": "1cfc3f7a-9b2f-4ee9-9d15-9883618b3218", 61       "id": "1cfc3f7a-9b2f-4ee9-9d15-9883618b3218",
            36       "image_display_url": "", 62       "image_display_url": "",
            37       "name": "depth-estimation", 63       "name": "depth-estimation",
            38       "title": "Depth Estimation" 64       "title": "Depth Estimation"
            n n 65     },
            66     {
            67       "description": "",
            68       "display_name": "Image Segmentation",
            69       "id": "7c8cc5f1-a9b2-4924-82ec-9e3aa3049a04",
            70       "image_display_url": "",
            71       "name": "image-segmentation",
            72       "title": "Image Segmentation"
            73     },
            74     {
            75       "description": "",
            76       "display_name": "Indoor Segmentation",
            77       "id": "83a1234f-7903-418d-8bed-9e6f085caaa0",
            78       "image_display_url": "",
            79       "name": "indoor-segmentation",
            80       "title": "Indoor Segmentation"
            81     },
            82     {
            83       "description": "",
            84       "display_name": "Monocular Depth Estimation",
            85       "id": "76f2b0b6-1665-4e60-9237-e546a2971c7c",
            86       "image_display_url": "",
            87       "name": "monocular-depth-estimation",
            88       "title": "Monocular Depth Estimation"
            39     } 89     }
            40   ], 90   ],
            41   "id": "7130a369-6155-4226-8c39-a69df85ac729", 91   "id": "7130a369-6155-4226-8c39-a69df85ac729",
            42   "isopen": false, 92   "isopen": false,
            n 43   "landing_page": "https://www.cs.nyu.edu/~ylclab/depth-v2.html", n 93   "landing_page": 
            94 "https://www.cs.nyu.edu/~ylclab/research/datasets/nyu_depth_v2.html",
            44   "license_title": null, 95   "license_title": null,
            45   "link_orkg": "", 96   "link_orkg": "",
            46   "metadata_created": "2024-12-02T23:10:51.098647", 97   "metadata_created": "2024-12-02T23:10:51.098647",
            n 47   "metadata_modified": "2024-12-02T23:10:51.800733", n 98   "metadata_modified": "2024-12-03T00:01:32.381477",
            48   "name": "nyu-depth-v2", 99   "name": "nyu-depth-v2",
            n 49   "notes": "The NYU Depth v2 dataset contains both RGB images and  n 100   "notes": "The NYU-Depth V2 dataset contains pairs of RGB and depth 
            50 depth maps taken by Microsoft Kinect from 464 different indoor scenes  101 images collected from Microsoft Kinect in 464 indoor scenes.",
            51 at resolution of 640x480.", 
            52   "num_resources": 1, 102   "num_resources": 0,
            53   "num_tags": 6, 103   "num_tags": 9,
            54   "organization": { 104   "organization": {
            55     "approval_status": "approved", 105     "approval_status": "approved",
            56     "created": "2024-11-25T12:11:38.292601", 106     "created": "2024-11-25T12:11:38.292601",
            57     "description": "", 107     "description": "",
            58     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", 108     "id": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            59     "image_url": "", 109     "image_url": "",
            60     "is_organization": true, 110     "is_organization": true,
            61     "name": "no-organization", 111     "name": "no-organization",
            62     "state": "active", 112     "state": "active",
            63     "title": "No Organization", 113     "title": "No Organization",
            64     "type": "organization" 114     "type": "organization"
            65   }, 115   },
            66   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", 116   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            67   "private": false, 117   "private": false,
            68   "relationships_as_object": [], 118   "relationships_as_object": [],
            69   "relationships_as_subject": [], 119   "relationships_as_subject": [],
            n 70   "resources": [ n 120   "resources": [],
            71     { 
            72       "cache_last_updated": null, 
            73       "cache_url": null, 
            74       "created": "2024-12-02T22:29:38", 
            75       "data": [ 
            76         "dcterms:title", 
            77         "dcterms:accessRights", 
            78         "dcterms:creator", 
            79         "dcterms:description", 
            80         "dcterms:issued", 
            81         "dcterms:language", 
            82         "dcterms:identifier", 
            83         "dcat:theme", 
            84         "dcterms:type", 
            85         "dcat:keyword", 
            86         "dcat:landingPage", 
            87         "dcterms:hasVersion", 
            88         "dcterms:format", 
            89         "mls:task" 
            90       ], 
            91       "description": "The json representation of the dataset with its  
            92 distributions based on DCAT.", 
            93       "format": "JSON", 
            94       "hash": "", 
            95       "id": "b3a8f7f6-dc98-4aef-9331-639df93b39b6", 
            96       "last_modified": "2024-12-02T23:10:51.793452", 
            97       "metadata_modified": "2024-12-02T23:10:51.803491", 
            98       "mimetype": "application/json", 
            99       "mimetype_inner": null, 
            100       "name": "Original Metadata", 
            101       "package_id": "7130a369-6155-4226-8c39-a69df85ac729", 
            102       "position": 0, 
            103       "resource_type": null, 
            104       "size": 795, 
            105       "state": "active", 
            106       "url":  
            107 resource/b3a8f7f6-dc98-4aef-9331-639df93b39b6/download/metadata.json", 
            108       "url_type": "upload" 
            109     } 
            110   ], 
            111   "services_used_list": "", 121   "services_used_list": "",
            112   "state": "active", 122   "state": "active",
            113   "tags": [ 123   "tags": [
            114     { 124     {
            n 115       "display_name": "Depth Maps", n 125       "display_name": "Benchmark",
            116       "id": "086c91f7-e8b5-4ec6-9988-31c1d244220c", 126       "id": "70474eb4-f8bf-42f1-bf26-7511d4f3356c",
            117       "name": "Depth Maps", 127       "name": "Benchmark",
            118       "state": "active", 128       "state": "active",
            119       "vocabulary_id": null 129       "vocabulary_id": null
            120     }, 130     },
            121     { 131     {
            n 122       "display_name": "Indoor Scenes", n 132       "display_name": "Indoor Segmentation",
            123       "id": "347c5737-e536-45b4-8044-796b0a7dc8f4", 133       "id": "873c9aba-d65e-4468-80f5-aabfe48d2c7d",
            124       "name": "Indoor Scenes", 134       "name": "Indoor Segmentation",
            125       "state": "active", 135       "state": "active",
            126       "vocabulary_id": null 136       "vocabulary_id": null
            127     }, 137     },
            128     { 138     {
            n 129       "display_name": "NYU Depth v2", n 139       "display_name": "Monocular Depth Estimation",
            130       "id": "73478843-c6b5-44a4-a035-32d7bc52aba4", 140       "id": "00d9c951-f01d-4cfd-aa97-eb1efc4edbe6",
            131       "name": "NYU Depth v2", 141       "name": "Monocular Depth Estimation",
            132       "state": "active", 142       "state": "active",
            133       "vocabulary_id": null 143       "vocabulary_id": null
            134     }, 144     },
            135     { 145     {
            n 136       "display_name": "RGB Images", n 146       "display_name": "NYU-Depth V2",
            137       "id": "5f8d12de-1380-449e-ba07-a8d556f501f6", 147       "id": "5aaf1752-057a-40a0-b055-91bd2716db73",
            138       "name": "RGB Images", 148       "name": "NYU-Depth V2",
            139       "state": "active", 149       "state": "active",
            140       "vocabulary_id": null 150       "vocabulary_id": null
            141     }, 151     },
            142     { 152     {
            n 143       "display_name": "computer vision", n 153       "display_name": "RGB-D",
            144       "id": "f650b4e3-9955-49b0-ba7b-2d302a990978", 154       "id": "b4388a5d-d31a-45b3-bd20-55ea8c48a7be",
            145       "name": "computer vision", 155       "name": "RGB-D",
            156       "state": "active",
            157       "vocabulary_id": null
            158     },
            159     {
            160       "display_name": "Support Inference",
            161       "id": "6438f64f-06af-4ce7-9ff5-6a744b57c8ea",
            162       "name": "Support Inference",
            146       "state": "active", 163       "state": "active",
            147       "vocabulary_id": null 164       "vocabulary_id": null
            148     }, 165     },
            149     { 166     {
            150       "display_name": "depth estimation", 167       "display_name": "depth estimation",
            151       "id": "3c08a798-cec3-4682-a668-4f95d6d8ad18", 168       "id": "3c08a798-cec3-4682-a668-4f95d6d8ad18",
            152       "name": "depth estimation", 169       "name": "depth estimation",
            153       "state": "active", 170       "state": "active",
            154       "vocabulary_id": null 171       "vocabulary_id": null
            n n 172     },
            173     {
            174       "display_name": "image segmentation",
            175       "id": "7eaed78e-c73a-4929-a8c9-60265069f59a",
            176       "name": "image segmentation",
            177       "state": "active",
            178       "vocabulary_id": null
            179     },
            180     {
            181       "display_name": "indoor scenes",
            182       "id": "7c39b0f6-b707-459a-9d7e-7e2625177b9f",
            183       "name": "indoor scenes",
            184       "state": "active",
            185       "vocabulary_id": null
            155     } 186     }
            156   ], 187   ],
            t 157   "title": "NYU Depth v2", t 188   "title": "NYU-Depth V2",
            158   "type": "dataset", 189   "type": "dataset",
            159   "version": "" 190   "version": ""
            160 } 191 }