Update README.md

README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+task_categories:
+- image-feature-extraction
+- image-classification
+- video-classification
+language:
+- en
+tags:
+- liveness detection
+- anti-spoofing
+- biometrics
+- facial recognition
+- machine learning
+- deep learning
+- AI
+- paper mask attack
+- iBeta certification
+- PAD attack
+- security
+- ibeta
+- face recognition
+- pad
+- authentication
+- fraud
+---
+7,000+ people, 70,000+ images: current selfies + archive photos 
+
+## Contact us and share your feedback - recieve additional samples for free! 😊
+
+## Real Multi-Year Temporal Coverage
+- Archive photos from 6 months to 10+ years before current images - not synthetic aging
+- Natural aging progression: wrinkles, hairstyle changes, weight fluctuations
+
+## Above-Average Photos Per Person
+- 8-15 archive photos (past) - historical photos from 1-15 years ago
+- 2-4 current selfies (present) - recent appearance with lighting and environment variations
+
+**Total: 70,000+ images across 7,000+ identities**
+
+## Diverse Real-World Conditions
+- Multi-device captures: Android, iOS, Windows (phones, webcams)
+- Multi-ethnic coverage: Balanced representation across demographics
+- Age range: 18-70 years old
+
+## Metadata Included
+- Demographics: gender, ethnicity, age
+- Device info: OS (Android/iOS/Windows), device type, model
+- Temporal data: archive photo years
+
+## Full version of dataset is availible for commercial usage - leave a request on our website [Axonlabs ](https://axonlabs.pro/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to purchase the dataset 💰
+
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F20109613%2F3517a12890c4f267b4bcc73093f00ee8%2FFrame%20170-2.png?generation=1768310109004948&alt=media)
+
+## Potential Use Cases
+- Face Recognition & Verification - High sample density per person for robust training
+- Temporal/Age-Invariant Recognition - Multi-year gaps for aging-robust models
+- Demographic Bias Testing - Balanced ethnic and age distribution
+- Cross-Device Training - Photos from multiple device types and resolutions
+- Long-term Identity Verification - Systems requiring recognition across years
+
+## Related Datasets with Additional Features
+This dataset focuses on temporal face recognition with current and archive selfies. For additional use cases, check out our related datasets:
+
+**[1. Selfie & Official ID Photo Dataset](https://huggingface.co/datasets/AxonData/Selfie_and_Official_ID_Photo_Dataset)**
+- Current and historical selfies PLUS official ID document photos (2 per person)
+- Ideal for: KYC verification, selfie-to-ID matching, identity verification
+- 6,000+ people with selfies + ID photos + archive photos
+- Use case: Training models to match casual selfies against official documents
+
+**[2. Face Recognition Dataset: Selfies & Videos](https://huggingface.co/datasets/AxonData/selfie-and-video-dataset)**
+- Same base dataset PLUS NIST liveness videos (2 per person: zoom-in + head turn)
+- Ideal for: Liveness detection, anti-spoofing, video face recognition
+- 1,000+ people with selfies + archive photos + liveness videos
+- Use case: Training models to detect presentation attacks and verify live persons
+
+keywords: face recognition, face detection, biometric authentication, liveness detection,
anti-spoofing, video face recognition, computer vision,
selfie dataset, video dataset