Standard DatasetsCharacters Relationship 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 "Characters Relationship Segmentation Dataset" is designed for the robotics and visual entertainment industries, featuring a wide range of internet-collected images with resolutions spanning from 1280 × 720 to 4608 × 3456. This unique dataset focuses on the relationships between humans, and between humans and objects, providing valuable insights for interaction dynamics.
Sample
Specification
Dataset ID
MD-Image-014
Dataset Name
Characters Relationship Segmentation Dataset
Data Type
ImageVolume
About 162.1k
Data Collection
Internet collected images, resolution ranges from 1280 × 720 to 4608 × 3456
Annotation
Semantic Segmentation,Relationship Segmentation
Annotation Notes
From the perspective of human as the main body, the relationship between human and human, between human and object, object type includes all the objects that interact with human.
Application Scenarios
Robot;Visual Entertainment
Data Collections
This dataset encompasses roughly 162.1k images, capturing the intricate relationships between individuals and between people and their surroundings. It includes a diverse array of objects that humans interact with, all annotated to detail the nature of these interactions. Ideal for developing advanced AI in robotics and enriching visual entertainment content, this dataset offers a nuanced understanding of character relationships and 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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