link
string
| type
string
|
|---|---|
"2d_masks/0.MOV" | "2d_mask" |
"2d_masks/2.MOV" | "2d_mask" |
"2d_masks/26.MOV" | "2d_mask" |
"2d_masks/16.mp4" | "2d_mask" |
"2d_masks/21.MOV" | "2d_mask" |
"2d_masks/18.mp4" | "2d_mask" |
"2d_masks/1.MOV" | "2d_mask" |
"2d_masks/13.mp4" | "2d_mask" |
"2d_masks/8.mp4" | "2d_mask" |
"2d_masks/7.MOV" | "2d_mask" |
"2d_masks/19.MOV" | "2d_mask" |
"2d_masks/27.mp4" | "2d_mask" |
"2d_masks/29.mp4" | "2d_mask" |
"2d_masks/3.MOV" | "2d_mask" |
"2d_masks/14.mp4" | "2d_mask" |
"2d_masks/10.mp4" | "2d_mask" |
"2d_masks/15.mp4" | "2d_mask" |
"2d_masks/22.mp4" | "2d_mask" |
"2d_masks/23.MOV" | "2d_mask" |
"2d_masks/6.MOV" | "2d_mask" |
"2d_masks/30.mp4" | "2d_mask" |
"2d_masks/28.MOV" | "2d_mask" |
"2d_masks/5.MOV" | "2d_mask" |
"2d_masks/4.MOV" | "2d_mask" |
"2d_masks/20.mp4" | "2d_mask" |
"2d_masks/11.mp4" | "2d_mask" |
"2d_masks/17.MOV" | "2d_mask" |
"2d_masks/25.mp4" | "2d_mask" |
"2d_masks/12.mp4" | "2d_mask" |
"2d_masks/31.MOV" | "2d_mask" |
"2d_masks/24.MOV" | "2d_mask" |
"2d_masks/9.mp4" | "2d_mask" |
"cut_masks/11.MOV" | "cut_mask" |
"cut_masks/0.MOV" | "cut_mask" |
"cut_masks/8.MOV" | "cut_mask" |
"cut_masks/12.MOV" | "cut_mask" |
"cut_masks/1.MOV" | "cut_mask" |
"cut_masks/13.mp4" | "cut_mask" |
"cut_masks/3.mp4" | "cut_mask" |
"cut_masks/14.mp4" | "cut_mask" |
"cut_masks/10.mp4" | "cut_mask" |
"cut_masks/15.MOV" | "cut_mask" |
"cut_masks/5.MOV" | "cut_mask" |
"cut_masks/4.MOV" | "cut_mask" |
"cut_masks/2.mp4" | "cut_mask" |
"cut_masks/6.mp4" | "cut_mask" |
"cut_masks/7.mp4" | "cut_mask" |
"cut_masks/9.mp4" | "cut_mask" |
Cut 2D Masks Presentation Attack Detection
The dataset consists of videos of individuals wearing printed 2D masks with cut-out holes for eyes, noses and mouths. Videos are filmed in different lightning conditions and in different places (indoors, outdoors), a person moves his/her head left, right, up and down. Each video in the dataset has an approximate duration of 7 seconds.
Types of videos in the dataset:
- 2d_mask - videos of the person wearing a printed 2D mask with cut-out holes for eyes.
- cut_mask - videos of the person wearing a printed 2D mask with cut-out holes for eyes, mouth and nose. All videos represent masks with holes for eyes, in some videos holes for both mouth and nose are made, in others only for mouth or nose.
.png?generation=1690468363734380&alt=media)
People in the dataset wear different accessorieses, such as glasses, caps, scarfs, hats and masks. Most of them are worn over a mask, however glasses and masks can be are also printed on the mask itself.
.png?generation=1690468790515642&alt=media)
The dataset serves as a valuable resource for computer vision, anti-spoofing tasks, video analysis, and security systems. It allows for the development of algorithms and models that can effectively detect attacks perpetrated by individuals wearing printed 2D masks.
Studying the dataset may lead to the development of improved security systems, surveillance technologies, and solutions to mitigate the risks associated with masked individuals carrying out attacks.
Get the dataset
This is just an example of the data
Leave a request on https://trainingdata.pro/data-market to discuss your requirements, learn about the price and buy the dataset.
Content
The dataset contains of two folders:
- 2d_masks contains videos of the person wearing a printed 2D mask with cut-out holes for eyes.
- cut_masks includes videos of the person wearing a printed 2D mask with cut-out holes for eyes, mouth and nose.
File with the extension .csv
- link: link to access the video,
- type: type of the attack: with printed 2D mask with cut-out holes for eyes OR with printed 2D mask with cut-out holes for eyes, mouth and nose
Attacks might be collected in accordance with your requirements.
**TrainingData**
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
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