Visual relationship dataset

1、VRD数据集

• VRD数据集用于图像中视觉关系的识别，数据集地址：https://cs.stanford.edu/people/ranjaykrishna/vrd/，整个数据集包括5000张图像，37993000个目标关系，70中目标关系（谓语）主要包括以下5类：
• 

结果展示：

• 数据集包括100个目标类别以及目标对应的70个关系类别，其中，

100个目标类别为：

1th object category: person，2th object category: sky，3th object category: building，

4th object category: truck，5th object category: bus，6th object category: table，

7th object category: shirt，8th object category: chair， 9th object category: car

10th object category: train，11th object category: glasses，12th object category: tree

13th object category: boat，14th object category: hat， 15th object category: trees

16th object category: grass，17th object category: pants，18th object category: road

19th object category: motorcycle，20th object category: jacket，21th object category: monitor

22th object category: wheel，23th object category: umbrella，24th object category: plate

25th object category: bike，26th object category: clock，27th object category: bag

28th object category: shoe，29th object category: laptop，30th object category: desk

31th object category: cabinet，32th object category: counter，33th object category: bench

34th object category: shoes，35th object category: tower，36th object category: bottle

37th object category: helmet，38th object category: stove，39th object category: lamp

40th object category: coat，41th object category: bed，42th object category: dog

43th object category: mountain，44th object category: horse，45th object category: plane

46th object category: roof，47th object category: skateboard，48th object category: traffic light

49th object category: bush，50th object category: phone，51th object category: airplane

52th object category: sofa，53th object category: cup，54th object category: sink

55th object category: shelf，56th object category: box，57th object category: van

58th object category: hand，59th object category: shorts，60th object category: post

61th object category: jeans，62th object category: cat， 63th object category: sunglasses

64th object category: bowl， 65th object category: computer，66th object category: pillow

67th object category: pizza，68th object category: basket，69th object category: elephant

70th object category: kite，71th object category: sand，72th object category: keyboard

73th object category: plant，74th object category: can，75th object category: vase，

76th object category: refrigerator，77th object category: cart，78th object category: skis

79th object category: po，80th object category: surfboard，81th object category: paper

82th object category: mouse，83th object category: trash can， 84th object category: cone

85th object category: camera，86th object category: ball，87th object category: bear

88th object category: giraffe，89th object category: tie，90th object category: luggage

91th object category: faucet，92th object category: hydrant，93th object category: snowboard

94th object category: oven，95th object category: engine，96th object category: watch

97th object category: face， 98th object category: street，99th object category: ramp

100th object category: suitcase

 

70个关系类别为：

1th predicate category: on，2th predicate category: wear，3th predicate category: has

4th predicate category: next to，5th predicate category: sleep next to，6th predicate category: sit next to

7th predicate category: stand next to，8th predicate category: park next，9th predicate category: walk next to

10th predicate category: above，11th predicate category: behind，12th predicate category: stand behind

13th predicate category: sit behind，14th predicate category: park behind，15th predicate category: in the front of

16th predicate category: under，17th predicate category: stand under，18th predicate category: sit under

19th predicate category: near， 20th predicate category: walk to，21th predicate category: walk

22th predicate category: walk past，23th predicate category: in，24th predicate category: below

25th predicate category: beside，26th predicate category: walk beside，27th predicate category: over

28th predicate category: hold，29th predicate category: by，30th predicate category: beneath

31th predicate category: with，32th predicate category: on the top of，33th predicate category: on the left of

34th predicate category: on the right of，35th predicate category: sit on，36th predicate category: ride

37th predicate category: carry，38th predicate category: look，39th predicate category: stand on

40th predicate category: use，41th predicate category: at，42th predicate category: attach to

43th predicate category: cover，44th predicate category: touch，45th predicate category: watch

46th predicate category: against，47th predicate category: inside，48th predicate category: adjacent to

49th predicate category: across，50th predicate category: contain，51th predicate category: drive

52th predicate category: drive on，53th predicate category: taller than，54th predicate category: eat

55th predicate category: park on，56th predicate category: lying on，57th predicate category: pull

58th predicate category: talk，59th predicate category: lean on，60th predicate category: fly

61th predicate category: face，62th predicate category: play with，63th predicate category: sleep on

64th predicate category: outside of，65th predicate category: rest on，66th predicate category: follow

67th predicate category: hit，68th predicate category: feed，69th predicate category: kick

70th predicate category: skate on

2、Visual Genome 数据

Visual Genome 数据集是斯坦福大学维护的图像及图像内容语义信息的数据集，相比于著名的 ImageNet 图像标注数据集（也由斯坦福大学维护），Visual Genome 数据集附加了更为丰富的语义信息，用以拓展更加丰富的基于图像及语义信息的  人工智能 应用。目前包括 108249 张图片、420 万区域内容描述（Region Descriptions）、170 万图像内容问答（Visual Question Answers）、210 万对象案例（Object Instances）、180 万属性（Attributes）、180 万关系（Relationships）。该数据集最初于 2015 年由斯坦福大学发布，而后 2016 年发布 1.2 版本，2017 年发布 1.4 版本。

在关系识别方向，目标的类别为200，关系的类别为100.

官网地址：http://visualgenome.org/

1. Images

• File image part1, image part2

  全部 jpg 格式的图片

2. Image meta data

• File image_data.json.zip

• 全部图片的 meta data，格式：

7. Relationships

• File relationships.json.zip

  全部的 relationships.