Microsoft COCO: Common Objects in Context View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2014

AUTHORS

Tsung-Yi Lin , Michael Maire , Serge Belongie , James Hays , Pietro Perona , Deva Ramanan , Piotr Dollár , C. Lawrence Zitnick

ABSTRACT

We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This is achieved by gathering images of complex everyday scenes containing common objects in their natural context. Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of 2.5 million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN. Finally, we provide baseline performance analysis for bounding box and segmentation detection results using a Deformable Parts Model. More... »

PAGES

740-755

Book

TITLE

Computer Vision – ECCV 2014

ISBN

978-3-319-10601-4
978-3-319-10602-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-10602-1_48

DOI

http://dx.doi.org/10.1007/978-3-319-10602-1_48

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045321436


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/17", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology and Cognitive Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1701", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Cornell, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Cornell, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lin", 
        "givenName": "Tsung-Yi", 
        "id": "sg:person.013735773703.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013735773703.86"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Caltech, USA", 
          "id": "http://www.grid.ac/institutes/grid.20861.3d", 
          "name": [
            "Caltech, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Maire", 
        "givenName": "Michael", 
        "id": "sg:person.01150451373.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01150451373.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cornell, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Cornell, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Belongie", 
        "givenName": "Serge", 
        "id": "sg:person.0632735744.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632735744.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brown, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Brown, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hays", 
        "givenName": "James", 
        "id": "sg:person.01140714336.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140714336.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Caltech, USA", 
          "id": "http://www.grid.ac/institutes/grid.20861.3d", 
          "name": [
            "Caltech, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Perona", 
        "givenName": "Pietro", 
        "id": "sg:person.01350615534.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350615534.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "UC Irvine, USA", 
          "id": "http://www.grid.ac/institutes/grid.266093.8", 
          "name": [
            "UC Irvine, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ramanan", 
        "givenName": "Deva", 
        "id": "sg:person.010041565404.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010041565404.26"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Microsoft Research, USA", 
          "id": "http://www.grid.ac/institutes/grid.419815.0", 
          "name": [
            "Microsoft Research, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Doll\u00e1r", 
        "givenName": "Piotr", 
        "id": "sg:person.0657122625.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657122625.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Microsoft Research, USA", 
          "id": "http://www.grid.ac/institutes/grid.419815.0", 
          "name": [
            "Microsoft Research, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zitnick", 
        "givenName": "C. Lawrence", 
        "id": "sg:person.012713070527.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012713070527.60"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2014", 
    "datePublishedReg": "2014-01-01", 
    "description": "We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This is achieved by gathering images of complex everyday scenes containing common objects in their natural context. Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of 2.5 million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN. Finally, we provide baseline performance analysis for bounding box and segmentation detection results using a Deformable Parts Model.", 
    "editor": [
      {
        "familyName": "Fleet", 
        "givenName": "David", 
        "type": "Person"
      }, 
      {
        "familyName": "Pajdla", 
        "givenName": "Tomas", 
        "type": "Person"
      }, 
      {
        "familyName": "Schiele", 
        "givenName": "Bernt", 
        "type": "Person"
      }, 
      {
        "familyName": "Tuytelaars", 
        "givenName": "Tinne", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-10602-1_48", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-319-10601-4", 
        "978-3-319-10602-1"
      ], 
      "name": "Computer Vision \u2013 ECCV 2014", 
      "type": "Book"
    }, 
    "keywords": [
      "instance segmentation", 
      "object recognition", 
      "novel user interface", 
      "deformable part model", 
      "baseline performance analysis", 
      "precise object localization", 
      "common objects", 
      "scene understanding", 
      "user interface", 
      "object localization", 
      "part model", 
      "category detection", 
      "object types", 
      "detection results", 
      "new dataset", 
      "performance analysis", 
      "datasets", 
      "segmentation", 
      "objects", 
      "everyday scenes", 
      "images", 
      "ImageNet", 
      "recognition", 
      "scene", 
      "Pascal", 
      "context", 
      "photos", 
      "interface", 
      "spotting", 
      "instances", 
      "art", 
      "creation", 
      "detection", 
      "goal", 
      "detailed statistical analysis", 
      "box", 
      "model", 
      "localization", 
      "natural context", 
      "analysis", 
      "results", 
      "questions", 
      "state", 
      "statistical analysis", 
      "types", 
      "comparison", 
      "understanding", 
      "broader questions", 
      "worker involvement", 
      "years", 
      "involvement", 
      "Sun", 
      "total", 
      "complex everyday scenes", 
      "extensive crowd worker involvement", 
      "crowd worker involvement", 
      "instance spotting", 
      "segmentation detection results"
    ], 
    "name": "Microsoft COCO: Common Objects in Context", 
    "pagination": "740-755", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1045321436"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-10602-1_48"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-10602-1_48", 
      "https://app.dimensions.ai/details/publication/pub.1045321436"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2021-12-01T20:04", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/chapter/chapter_296.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-10602-1_48"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10602-1_48'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10602-1_48'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10602-1_48'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10602-1_48'


 

This table displays all metadata directly associated to this object as RDF triples.

193 TRIPLES      23 PREDICATES      84 URIs      77 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-10602-1_48 schema:about anzsrc-for:17
2 anzsrc-for:1701
3 schema:author N7ffbb4e265b74450aba594e6e3f6e9a5
4 schema:datePublished 2014
5 schema:datePublishedReg 2014-01-01
6 schema:description We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This is achieved by gathering images of complex everyday scenes containing common objects in their natural context. Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of 2.5 million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN. Finally, we provide baseline performance analysis for bounding box and segmentation detection results using a Deformable Parts Model.
7 schema:editor N50ae17a9addb48f2b2b3365cd49121db
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree true
11 schema:isPartOf Na0c509533c7747208cffa2a65579b718
12 schema:keywords ImageNet
13 Pascal
14 Sun
15 analysis
16 art
17 baseline performance analysis
18 box
19 broader questions
20 category detection
21 common objects
22 comparison
23 complex everyday scenes
24 context
25 creation
26 crowd worker involvement
27 datasets
28 deformable part model
29 detailed statistical analysis
30 detection
31 detection results
32 everyday scenes
33 extensive crowd worker involvement
34 goal
35 images
36 instance segmentation
37 instance spotting
38 instances
39 interface
40 involvement
41 localization
42 model
43 natural context
44 new dataset
45 novel user interface
46 object localization
47 object recognition
48 object types
49 objects
50 part model
51 performance analysis
52 photos
53 precise object localization
54 questions
55 recognition
56 results
57 scene
58 scene understanding
59 segmentation
60 segmentation detection results
61 spotting
62 state
63 statistical analysis
64 total
65 types
66 understanding
67 user interface
68 worker involvement
69 years
70 schema:name Microsoft COCO: Common Objects in Context
71 schema:pagination 740-755
72 schema:productId N09aa237c50fa4558abd1ef879597f42d
73 Na40fc30c23894156aa9ca0a9714cecab
74 schema:publisher Na8d8b8af54b94f7fb386522833dbdd53
75 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045321436
76 https://doi.org/10.1007/978-3-319-10602-1_48
77 schema:sdDatePublished 2021-12-01T20:04
78 schema:sdLicense https://scigraph.springernature.com/explorer/license/
79 schema:sdPublisher Nbbfd830bbb404115bec234ef9ee23a48
80 schema:url https://doi.org/10.1007/978-3-319-10602-1_48
81 sgo:license sg:explorer/license/
82 sgo:sdDataset chapters
83 rdf:type schema:Chapter
84 N04054581048c4851b5cf39e08f33e8f7 rdf:first sg:person.01150451373.69
85 rdf:rest N43c85fc1ff74447ebd2fc23b6e3be7e3
86 N09aa237c50fa4558abd1ef879597f42d schema:name doi
87 schema:value 10.1007/978-3-319-10602-1_48
88 rdf:type schema:PropertyValue
89 N2b175651de464b65b8c70b995eb4c7e6 rdf:first sg:person.0657122625.46
90 rdf:rest N3a97775a5d524a96955e02a157445f06
91 N3a97775a5d524a96955e02a157445f06 rdf:first sg:person.012713070527.60
92 rdf:rest rdf:nil
93 N3cc4e46629c241b9b61eb15a0a5ecfdd schema:familyName Schiele
94 schema:givenName Bernt
95 rdf:type schema:Person
96 N43c85fc1ff74447ebd2fc23b6e3be7e3 rdf:first sg:person.0632735744.68
97 rdf:rest Nddd7a2aa69ea473d892b67040ef3064e
98 N50ae17a9addb48f2b2b3365cd49121db rdf:first N682709a204f4412990679f78b3196aee
99 rdf:rest N84310ef5b8294c45b3c6c9a515999872
100 N682709a204f4412990679f78b3196aee schema:familyName Fleet
101 schema:givenName David
102 rdf:type schema:Person
103 N7ffbb4e265b74450aba594e6e3f6e9a5 rdf:first sg:person.013735773703.86
104 rdf:rest N04054581048c4851b5cf39e08f33e8f7
105 N84310ef5b8294c45b3c6c9a515999872 rdf:first Ndee3210d57ee42b99fe06db956bbef36
106 rdf:rest N9f97570bbf764ae8b5245be42f87316d
107 N9f1b251ec5e34e9ca5507b0237411db8 rdf:first sg:person.01350615534.24
108 rdf:rest Nb3b1169cc065428abb9cab88f1ebcb91
109 N9f97570bbf764ae8b5245be42f87316d rdf:first N3cc4e46629c241b9b61eb15a0a5ecfdd
110 rdf:rest Nda9c309ce59c4b2ab3b11fcaf9323033
111 Na0c509533c7747208cffa2a65579b718 schema:isbn 978-3-319-10601-4
112 978-3-319-10602-1
113 schema:name Computer Vision – ECCV 2014
114 rdf:type schema:Book
115 Na40fc30c23894156aa9ca0a9714cecab schema:name dimensions_id
116 schema:value pub.1045321436
117 rdf:type schema:PropertyValue
118 Na8d8b8af54b94f7fb386522833dbdd53 schema:name Springer Nature
119 rdf:type schema:Organisation
120 Nb3b1169cc065428abb9cab88f1ebcb91 rdf:first sg:person.010041565404.26
121 rdf:rest N2b175651de464b65b8c70b995eb4c7e6
122 Nbbfd830bbb404115bec234ef9ee23a48 schema:name Springer Nature - SN SciGraph project
123 rdf:type schema:Organization
124 Nda9c309ce59c4b2ab3b11fcaf9323033 rdf:first Nfcd9a3585ee44561905eb94fce6a0b39
125 rdf:rest rdf:nil
126 Nddd7a2aa69ea473d892b67040ef3064e rdf:first sg:person.01140714336.50
127 rdf:rest N9f1b251ec5e34e9ca5507b0237411db8
128 Ndee3210d57ee42b99fe06db956bbef36 schema:familyName Pajdla
129 schema:givenName Tomas
130 rdf:type schema:Person
131 Nfcd9a3585ee44561905eb94fce6a0b39 schema:familyName Tuytelaars
132 schema:givenName Tinne
133 rdf:type schema:Person
134 anzsrc-for:17 schema:inDefinedTermSet anzsrc-for:
135 schema:name Psychology and Cognitive Sciences
136 rdf:type schema:DefinedTerm
137 anzsrc-for:1701 schema:inDefinedTermSet anzsrc-for:
138 schema:name Psychology
139 rdf:type schema:DefinedTerm
140 sg:person.010041565404.26 schema:affiliation grid-institutes:grid.266093.8
141 schema:familyName Ramanan
142 schema:givenName Deva
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010041565404.26
144 rdf:type schema:Person
145 sg:person.01140714336.50 schema:affiliation grid-institutes:None
146 schema:familyName Hays
147 schema:givenName James
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140714336.50
149 rdf:type schema:Person
150 sg:person.01150451373.69 schema:affiliation grid-institutes:grid.20861.3d
151 schema:familyName Maire
152 schema:givenName Michael
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01150451373.69
154 rdf:type schema:Person
155 sg:person.012713070527.60 schema:affiliation grid-institutes:grid.419815.0
156 schema:familyName Zitnick
157 schema:givenName C. Lawrence
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012713070527.60
159 rdf:type schema:Person
160 sg:person.01350615534.24 schema:affiliation grid-institutes:grid.20861.3d
161 schema:familyName Perona
162 schema:givenName Pietro
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350615534.24
164 rdf:type schema:Person
165 sg:person.013735773703.86 schema:affiliation grid-institutes:None
166 schema:familyName Lin
167 schema:givenName Tsung-Yi
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013735773703.86
169 rdf:type schema:Person
170 sg:person.0632735744.68 schema:affiliation grid-institutes:None
171 schema:familyName Belongie
172 schema:givenName Serge
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632735744.68
174 rdf:type schema:Person
175 sg:person.0657122625.46 schema:affiliation grid-institutes:grid.419815.0
176 schema:familyName Dollár
177 schema:givenName Piotr
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657122625.46
179 rdf:type schema:Person
180 grid-institutes:None schema:alternateName Brown, USA
181 Cornell, USA
182 schema:name Brown, USA
183 Cornell, USA
184 rdf:type schema:Organization
185 grid-institutes:grid.20861.3d schema:alternateName Caltech, USA
186 schema:name Caltech, USA
187 rdf:type schema:Organization
188 grid-institutes:grid.266093.8 schema:alternateName UC Irvine, USA
189 schema:name UC Irvine, USA
190 rdf:type schema:Organization
191 grid-institutes:grid.419815.0 schema:alternateName Microsoft Research, USA
192 schema:name Microsoft Research, USA
193 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...