Face Recognition Images with Gauze Masks Across Conditions

Featuring 5,030 face images from 7 images per person, featuring individuals wearing gauze masks. It includes multiple mask types, age groups, lighting conditions, and scenes. The data is intended for occluded face detection and recognition tasks.

Use Cases

• Train an occluded face detection model using images with multiple mask types.
• Develop face recognition algorithms robust to variations in light conditions and scenes.
• Analyze model performance across different age groups present in the dataset.
• Benchmark computer vision models on a dataset containing 5,030 images with gauze mask occlusions.

Strengths

• Contains 5,030 face images, providing a sample for model training and testing.
• Includes 7 images per person, allowing for intra-person variation analysis.
• Features multiple controlled variations: mask types, ages, light conditions, and scenes.

Limitations

• The dataset is described as a sample of a larger paid dataset, limiting its scale and completeness.
• Specific details on image resolution, annotation format, and demographic distribution are unavailable.
• The sample size of 5,030 images may be insufficient for training deep learning models from scratch without augmentation or transfer learning.

Provenance

Source

Nexdata via Hugging Face.

Collection Method

Collected images of individuals wearing gauze masks.

Freshness

Last updated on 2025-04-24.

Geography

Region tag indicates 'us', but specific geographic coverage is unknown.