Update README.md

README.md

@@ -1,3 +1,44 @@
----
-license: cc-by-nc-nd-4.0
----
+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- video-classification
+tags:
+- Machine learning
+- Security
+- Anti-spoofing
+- Liveness Detection
+- Biometric Verification
+size_categories:
+- 10K<n<100K
+---
+# 2D Mask Attack Dataset - 26 436 videos
+The dataset comprises **26,436** videos of real faces, **2D print attacks** (printed photos), and **replay attacks** (faces displayed on screens), captured under varied conditions. Designed for **attack detection** research, it supports the development of robust **face antispoofing** and **spoofing detection** methods, critical for **facial recognition security**. — **[Get the data](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset)**
+## Dataset characteristics:
+| Characteristic          | Data                                                                                             |
+|-------------------------|--------------------------------------------------------------------------------------------------|
+| Description             | Videos of individuals with printed masks and replay attacks                                      |
+| Data types              | Video                                                                                            |
+| Tasks                   | Anti-spoofing, Liveness Detection, Face Recognition                                              |
+| Number of videos        | 26,436                                                                                           |
+| Name of categories      | Video fakes, tolokers based spoofs, video zoom, youdo heads, in-car videos and fakes             |
+| Labeling                | Metadata (age, gender, ethnicity)                                                                |
+| Gender                  | Male, Female                                                                                     |
+
+### 📊 Sample dataset available! For full access, [contact us](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset) to discuss purchase terms.
+
+## Dataset structure
+- in_car_videos_and_fakes  —  Videos of crowdworkers' faces, captured inside cars, shown on phone screens.
+- toloka_video_fakes — Videos of crowdworkers' faces displayed on computer or phone screens
+- tolokers_based_spoofs — Videos of crowdworkers' faces displayed on computer or phone screens
+- video_zoom — A zoom-based spoofing attack
+- youdo_heads — Videos of cut-out color printouts of faces, collected via YouDo
+- 2D Printed Mask Attacks and Replay Attacks Videos Dataset.csv — file contains metadata for all individuals in the dataset.
+
+### 🧩 Like the dataset but need different data? We can collect a custom dataset just for you - learn more about our data collection services [here](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset)
+
+## Similar Datasets:
+1. [iBeta Level 1 Dataset](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset)
+2. [2D Print Attacks and Silicone Masks Attacks Dataset](https://unidata.pro/datasets/2d-print-attacks-and-silicone-masks-attacks-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset)
+3. [2D Printed Photos Attacks and Replay Attacks Images Dataset](https://unidata.pro/datasets/2d-printed-photos-attacks-and-replay-attacks-images-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset)
+
+## 🌐 [UniData](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-biometrics&utm_medium=referral&utm_campaign=2D-mask-attack-dataset) - your trusted data partner. Unique, accurate, thoroughly collected and annotated data designed to fuel your AI/ML success.