---
license: cc-by-nc-nd-4.0
task_categories:
- video-classification
language:
- en
tags:
- finance
- legal
- code
dataset_info:
  features:
  - name: live_video_id
    dtype: string
  - name: phone
    dtype: string
  - name: video_file
    dtype: string
  - name: phone_video_playback
    dtype: string
  - name: worker_id
    dtype: string
  splits:
  - name: train
    num_bytes: 5063
    num_examples: 30
  download_size: 735628032
  dataset_size: 5063
---
# Antispoofing Replay - Biometric Attack dataset
The dataset consists of 30,000+ videos of replay attacks from people from 157 countries. 
It is based on data from **Anti Spoofing Real Dataset**: https://www.kaggle.com/datasets/trainingdatapro/anti-spoofing-live. 

The anti spoofing dataset includes: **replay attacks** - videos from Antispoofing Real filmed on the phone.

The videos were gathered by capturing faces of genuine individuals presenting spoofs, using facial presentations. Our dataset proposes a novel approach that learns and detects spoofing techniques, extracting features from the genuine facial images to prevent the capturing of such information by fake users. 

The dataset contains images and videos of real humans with various **resolutions, views, and colors**, making it a comprehensive resource for researchers working on anti-spoofing technologies.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0fe0cca9d56fd2c013589667097b24b9%2Freplay.png?generation=1685095721064910&alt=media)

The dataset provides data to combine and apply different techniques, approaches, and models to address the challenging task of distinguishing between genuine and spoofed inputs, providing effective anti-spoofing solutions in active authentication systems. These solutions are crucial as newer devices, such as phones, have become vulnerable to spoofing attacks due to the availability of technologies that can create replays, reflections, and depths, making them susceptible to spoofing and generalization. 

Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models. 

# 💴 For Commercial Usage: Full version of the dataset includes 30 000+ videos, leave a request on **[TrainingData](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay)** to buy the dataset

### Metadata for the full dataset:
- **replay.assignment_id** - unique identifier of the media file
- **real_assignment_id**- unique identifier of the media file from the [Antispoofing Real Dataset](https://trainingdata.pro/datasets/anti-spoofing-real?utm_source=huggingface&utm_medium=cpc&utm_campaign=antispoofing-replay-dataset)
- **worker_id** - unique identifier of the person
- **age** - age of the person
- **true_gender** - gender of the person
- **country** - country of the person
- **ethnicity** - ethnicity of the person
- **video_extension** - video extensions in the dataset
- **video_resolution** - video resolution in the dataset
- **video_duration** - video duration in the dataset
- **video_fps** - frames per second for video in the dataset

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay) to discuss your requirements, learn about the price and buy the dataset**

# Content
### The folder **"samples"** includes 30 folders:
- corresponding to each person in the sample
- containing of the video of replay attack 

### File with the extension .csv
includes the following information for each media file:
- **live_video_id**: the unique identifier of the "Antispoofing Live" video
- **phone**: the device used to capture the replay video,
- **link**: the URL to access the replay video,
- **phone_video_payback**: the device used to play the "Antispoofing Live" video,
- **worker_id**: the identifier of the person who provided the media file,

**[TrainingData](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay)** provides high-quality data annotation tailored to your needs.

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**

*keywords: ibeta level 1, ibeta level 2, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, video replay attack, replay attack dataset, replay attack database, replay mobile dataset, video attack attempts, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, phone attack dataset, face anti spoofing, large-scale face anti spoofing, rich annotations anti spoofing dataset, replay spoof attack, display spoof attack*