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Computer Vision Datasets

Instantly enhance AI model performance with high quality off-the-shelf datasets.

Task Type

All
32
Age
2
Clothing Detection
2
Clothing Segmentation
1
Event Detection
9
Expression
6
Face Anti-spoofing
6
Face Recognition
29
Face Segmentation
1
Facial Landmark
4
Gait Recognition
3
Garbage Classification
1
Gesture Recognition
6
Human Body Attribute
4
Human Body Detection
6
Human Body Landmark
3
Human Body Segmentation
7
Human Body Tracking
3
Human Pose
25
Image Processing
1
Infrared Face
1
Makeup
1
Object Detection and Classification
3
Occluded Face
2
Others
23
Person Re-Identification
4
Pet Recognition
2
Refined Urban Management
4
Scene Understanding
4
Skin Defects
1
Unlabeled Data
11
Vehicle Re-Identification
1
Vehicle Recognition
2
3D Face
4

Modalities

All
32
Image
86
Video
46

602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data

602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data,The data diversity includes headphones, body, background,and glasses.In terms of annotation, we adpoted segmentation annotations on headphones, body, background and glasses.The data can be used for tasks such as human body segmentation and the behavior detection of Video conference.
Human body segmentation different poses different ages different races different collection backgrounds different scenes.

4,290 Images – Occluded Human Body Collection Data

4,290 Images – Occluded Human Body Collection Data. There are 2-5 occluded human bodies for each images. The age distribution is ranging from children to the elderly, the middle-aged and young people are the majorities. The race distribution is Asian. The data diversity includs multiple scenes, multiple age groups, multiple occluded between human bodies, multiple human body postures. The data can be used for tasks such as occluded human body detection and segmentation.
occluded human body indoor scenes outdoor scenes multiple scenes multiple age groups multiple occluded between human bodies multiple human body postures occluded human body detection and segmentation

18,880 Images of 466 People - 3D Instance Segmentation and 22 Landmarks Annotation Data of Human Body

18,880 Images of 466 People - 3D Instance Segmentation and 22 Landmarks Annotation Data of Human Body. The dataset diversity includes multiple scenes, light conditions, ages, shooting angles, and poses. In terms of annotation, we adpoted instance segmentation annotations on human body. 22 landmarks were also annotated for each human body. The dataset can be used for tasks such as human body instance segmentation and human behavior recognition.
Human body instance segmentation Human body landmarks 3D Multiple poses Multiple scenes

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes. The data includes indoor (shopping mall) and outdoor (street, the gate of shopping mall and square) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 19 attributes of human body were annotated. The data can be used for person attributes recognition.
indoor and outdoor scenes human body bounding boxes appendage bounding boxes surveillance camera multiple age groups human body attributes

34,981 Images – Alpha Matte Human Body Segmentation Data (Fine Version)

34,981 Images – Alpha Matte Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The dataset diversity includes multiple scenes, multiple age groups, multiple human body angles, multiple postures. In terms of annotation, alpha matte segmentation annotation was adopted for the human body. The data can be used for tasks such as alpha matte human body segmentation.
Alpha matte human body segmentation multiple scenes multiple age groups multiple human body angles multiple postures

25,080 Images – Alpha Matte Human Body Segmentation Data (Basic Version)

25,080 Images – Alpha Matte Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The dataset diversity includes multiple scenes, multiple age groups, multiple human body angles, multiple postures. In terms of annotation, alpha matte segmentation annotation was adopted for the human body. The data can be used for tasks such as alpha matte human body segmentation.
Alpha matte human body segmentation multiple scenes multiple age groups multiple human body angles multiple postures

21,300 Images - Human Body Segmentation Data

21,300 Images - Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The data covers female people and male people. The race distribution includes Asian, black race and Caucasian. The age distribution ranges from teenager to the elderly, the middle-aged and young people are the majorities. The dataset diversity includes multiple scenes, ages, races, postures, and appendages. In terms of annotation, we adpoted pixel-wise segmentation annotations on human body. The data can be used for tasks such as human body segmentation.
Multiple scenes Multiple ages Multiple races Multiple postures Multiple appendages

15 People - 22 Landmarks Annotation Data of 3D Human Body

15 People - 22 Landmarks Annotation Data of 3D Human Body. The dataset diversity includes multiple scenes, different ages, different costumes, different human body sitting postures. In terms of annotation, we annotate the 2D and 3D coordinates of the 22 landmarks of the human body, landmark attributes, the rectangular frame of the human body. The dataset can be used for tasks such as human body instance segmentation and human behavior recognition.
Human body instance segmentation Human body landmarks 3D Multiple poses Multiple scenes

50,356 Images - Human Body Segmentation and 18 Landmarks Data

50,356 Images - Human Body Segmentation and 18 Landmarks Data. The data diversity includes multiple scenes, ages, races, poses, and appendages. In terms of annotation, we adpoted segmentation annotations on human body and appendages.18 landmarks were also annotated for each human body. The data can be used for tasks such as human body segmentation and human behavior recognition.
Human body segmentation Landmark Multiple races Multiples postures Multiple scenes
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