Standard DatasetsLive Streamer Portrait 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 "Live Streamer Portrait Segmentation Dataset" is tailored for the media and entertainment industry, consisting of screenshots from live streams with resolution sizes ranging from 540 x 960 to 720 x 1280 pixels. This dataset focuses on contour segmentation, distinguishing between the human body (specifically the live streamer) and the background, aiming to enhance content personalization and viewer engagement in live streaming platforms.
Sample
Specification
Dataset ID
MD-Image-056
Dataset Name
Live Streamer Portrait Segmentation Dataset
Data Type
ImageVolume
About 15.6k
Data Collection
Live stream screenshot. Resolution sizes from 540*960 to 720*1280
Annotation
Contour Segmentation
Annotation Notes
Segmentation of Human body and background.
Application Scenarios
Media & Entertainment
Data Collections
This dataset includes approximately 15.6k images, each providing clear segmentation between the live streamer and the background. Such detailed segmentation is crucial for applications looking to apply virtual backgrounds, augmented reality effects, or for analytics purposes in assessing engagement based on the streamer's presence and activity. The dataset supports the development of advanced content creation tools and interactive features, elevating the live streaming experience for both streamers and viewers.
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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