UniDataPro commited on
Commit
ae23094
1 Parent(s): 8a1c9c4

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +38 -3
README.md CHANGED
@@ -1,3 +1,38 @@
1
- ---
2
- license: cc-by-nc-nd-4.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-nd-4.0
3
+ task_categories:
4
+ - video-classification
5
+ tags:
6
+ - people
7
+ - mask
8
+ - computer vison
9
+ - facial recognition
10
+ - verification
11
+ - cyber security
12
+ size_categories:
13
+ - 1K<n<10K
14
+ ---
15
+ # 2D Masks Attack for facial recogniton system
16
+ The dataset consists of **4,800+** videos of people wearing of holding 2D printed masks filmed using **5** devices. It is designed for **liveness detection** algorithms, specifically aimed at enhancing **anti-spoofing** capabilities in **biometric security** systems.
17
+
18
+ By leveraging this dataset, researchers can create more sophisticated recognition system, crucial for achieving **iBeta Level 1 & 2 certification** – a key standard for secure and reliable biometric systems designed to combat spoofing and fraud. - **[Get the data](https://unidata.pro/datasets/2d-masks-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-attacks)**
19
+ ## Attacks in the dataset
20
+ ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F832f7a434f528f526c5b89ca0bd7d265%2FFrame%20164.png?generation=1731112808397217&alt=media)
21
+ The attacks were recorded in diverse settings, showcasing individuals with various attributes. Each video includes human faces adorned with 2D printed masks to mimic potential spoofing attempts in facial recognition systems.
22
+
23
+ **Variants of backgrounds and attributes in the dataset**:
24
+ ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Fbf3ed70a8a519ebb4bbdd8fc634bd4f3%2FFrame%20146%20(2).png?generation=1730208154622175&alt=media)
25
+ # 💵 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/2d-masks-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-attacks) to discuss your requirements and pricing options.
26
+
27
+ ## Metadata for the dataset
28
+ ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Fa3501113f10d6a4edd27b3b9b5f94a52%2FFrame%20161%20(2).png?generation=1731112546935385&alt=media)
29
+
30
+ **Variables in .csv files:**
31
+
32
+ - **name:** filename of the printed 2D mask
33
+ - **path:** link-path for the original video
34
+ - **type:** type(wearing or holding) of printed mask
35
+
36
+ Researchers are developing advanced anti-spoofing detection techniques to enhance security systems against attacks using face masks.This focus on face masks allows researchers to train and test detection algorithms specifically designed to differentiate between genuine human faces and these increasingly sophisticated mask-based spoofing attempts.
37
+
38
+ # 🌐 [UniData](https://unidata.pro/datasets/2d-masks-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-attacks) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects