Delete README.md with huggingface_hub

README.md

@@ -1,26 +0,0 @@
----
-license: cc-by-nc-nd-4.0
-task_categories:
-- video-classification
-tags:
-- people
-- mask
-- computer vison
-- facial recognition
-- verification
-- cyber security
-size_categories:
-- 1K<n<10K
----
-# 3D Mask Attack for detection methods
-Dataset comprises **3,500+** videos captured using **5** different devices, featuring individuals holding photo fixed on cylinder designed to simulate potential presentation attacks against **facial recognition** systems. It supports research in attack detection and improves **spoofing detection** techniques, specifically for fraud prevention and compliance with **iBeta Level 1 certification** standards.
-
-By utilizing this dataset, researchers can enhance **liveness detection** and improve face presentation techniques, ultimately contributing to more robust **biometric security** measures.  - **[Get the data](https://unidata.pro/datasets/printed-3d-masks-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=3d-mask-attack)**
-## Attacks in the dataset
-![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F9285679c599b165bba3e5e37291175e4%2FFrame%20168.png?generation=1731895573047353&alt=media)
-# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/printed-3d-masks-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=3d-masks-attacks) to discuss your requirements and pricing options.
-Researchers can utilize this dataset to explore detection technology and recognition algorithms that aim to prevent impostor attacks and improve authentication processes.
-## Metadata for the dataset
-![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Faa4f1e847d71d64507b1009754d64464%2FFrame%20136.png?generation=1731895801179302&alt=media)
-This dataset serves as a crucial tool for enhancing liveness detection technologies and developing effective anti-spoofing algorithms, which are essential for maintaining the integrity of biometric verification processes.
-# 🌐 [UniData](https://unidata.pro/datasets/printed-3d-masks-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=3d-masks-attacks) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects