Standard DatasetsMulti-person And Appendages Segmentation Dataset
Advanced datasets and Generative AI are revolutionizing the fashion and e-commerce industries, providing customized experiences and immersive interactions for shoppers worldwide.Our datasets provide valuable insights into fashion trends, styles, and consumer preferences, enabling businesses to deliver personalized shopping experiences.
The "Multi-person And Appendages Segmentation Dataset" is designed for the visual entertainment sector, featuring a collection of internet-collected images with resolutions exceeding 2736 x 3648 pixels. This dataset employs both instance and semantic segmentation techniques to annotate multiple people and their appendages in various scenes. The appendages include shadows, hand-held objects, riding objects, and more, providing a comprehensive view of human interactions with their environment.
Sample
Specification
Dataset ID
MD-Image-069
Dataset Name
Multi-person And Appendages Segmentation Dataset
Data Type
ImageVolume
About 7k
Data Collection
Internet collected images. Resolution is over 2736 x 3648.
Annotation
Semantic Segmentation,Instance Segmentation
Annotation Notes
Annotate multi-person and appendages , appendages include shadows,hand-held objects, riding objects, etc.
Application Scenarios
Visual Entertainment
Data Collections
This dataset comprises approximately 7k images, each annotated to identify multiple individuals and their appendages, offering a detailed analysis of human figures and the objects they interact with, including shadows and items they might be holding or riding. The precise segmentation of both people and associated appendages makes this dataset invaluable for creating realistic and interactive scenes in visual entertainment, such as in video games, films, and AR/VR applications, enhancing the immersive experience by accurately representing human-object interactions.
Quality Assurance
Relevant Open Datasets
To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:
Fashionpedia [Learn more]
This dataset includes 48,825 clothing images annotated with segmentation masks and fine-grained attributes, built upon an expertly crafted ontology that encompasses 27 main apparel categories and 19 apparel parts. It's designed to advance tasks combining both detection and attributes classification in the fashion domain.
DeepFashion2 [Learn more]
A comprehensive fashion dataset containing 491K images of 13 popular clothing categories from both commercial and consumer sources. Each item is meticulously labeled with attributes such as scale, occlusion, viewpoint, category, and style, making it a versatile benchmark for clothing image understanding.
DeepFashion [Learn more]
This dataset boasts around 800K diverse fashion images with rich annotations, including 46 categories, 1,000 descriptive attributes, bounding boxes, and landmark information. The variety ranges from well-posed product images to consumer photos, providing a broad spectrum for fashion image analysis.
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