Standard DatasetsFacial Parts Semantic Segmentation Dataset
The progress of video and photo editing applications relies heavily on high-quality datasets for machine learning models training. Our carefully selected datasets play a crucial role in enhancing the abilities of such applications, by offering accurate segmentation and recognition of different elements within images and videos.
The Facial Parts Semantic Segmentation Dataset offers a vast collection of images with detailed annotations for facial feature segmentation. This dataset is designed to support media & entertainment and beauty sectors, featuring high-resolution images sourced both online and offline. It includes comprehensive categories such as eyes, eyebrows, nose, mouth, hair, and accessories, making it an essential facial segmentation dataset for AI-driven applications.
Sample
Specification
Dataset ID
MD-Image-019
Dataset Name
Facial Parts Semantic Segmentation Dataset
Data Type
ImageVolume
About 2,791.7k
Data Collection
Images collected from online and offline, resolution ranges from 300 x 300 to 4480 x 6720.
Annotation
Semantic Segmentation,Bounding Box
Annotation Notes
Face area categories include skin, left eye, right eye, left eyebrow, right eyebrow, nose, left ear, right ear, mouth, upper lip, lower lip, hair, cap, glasses, wearing accessories, neck, clothing, etc.
Application Scenarios
Media & Entertainment;Beauty
Data Collections
Encompassing approximately 2,791.7k images, this dataset provides an extensive examination of facial features, including skin, eyes, ears, mouth, and associated accessories like glasses and caps. The detailed annotations facilitate precise segmentation of each facial component, making it an invaluable resource for applications in beauty enhancements, virtual try-ons, and interactive media, by offering an in-depth understanding of facial anatomy and aesthetics.
Data Applitcation
● Augmented Reality: Enhance AR applications with detailed facial parts segmentation.
● Security Systems: Improve security and surveillance with precise facial analysis.
● Healthcare: Support diagnostic tools with comprehensive facial part analysis.
Why choose our Facial Parts Semantic Segmentation Dataset
● Comprehensive Annotations: Detailed segmentation across multiple facial features, including eyes, mouth, and hair.
● High Resolution: Images ranging from 300x300 to 4480x6720, ideal for AI training and media applications.
● Versatile Applications: Suitable for media, beauty, AI, and machine learning projects.
Quality Assurance
Relevant Open Datasets
To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:
FASSEG Repository [Learn more]
This collection offers datasets for frontal face segmentation (Frontal01 and Frontal02) and a dataset for faces in multiple poses (Multipose01).These datasets can be valuable for training models to perform face segmentation in different orientations and conditions.
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