--- title: "Anti-Spoofing Replay Phone Videos Dataset" description: "This anti-spoofing dataset contains over 40,036 live facial video recordings captured on mobile devices to support replay attack detection and biometric anti-spoofing research. With paired…" url: "https://unidata.pro/datasets/anti-spoofing-replay-phone-videos/" date_modified: "2025-12-25T10:22:26+03:00" language: "en-US" --- This anti-spoofing dataset contains over 40,036 live facial video recordings captured on mobile devices to support replay attack detection and biometric anti-spoofing research. With paired video sets, MP4/MOV formats, and rich metadata such as age, gender, and ethnicity, it provides reliable training data for face antispoofing, liveness detection, and secure biometric authentication systems. ## Dataset Structure ### The Numbers Section **Numbered list:** - **Number:** 40,036 — **Text:** Videos - **Number:** 20,018 — **Text:** Sets ### Tooltips Section **Tooltip items:** - **Name:** Facial Recognition - **Name:** Liveness Detection - **Name:** Security - **Name:** Anti-spoofing - **Name:** Computer Vision ### Dataset Information **Table with data:** | Characteristic | Data | | --- | --- | | Description | Live videos of people for anti-spoofing tasks | | Data types | Video | | Tasks | Face recognition, Face detection | | Number of sets | 20,018 | | Number of videos | 40,036 | | Number of files in a set | 2 videos | | Labeling | Only technical characteristics and metadata (age, gender, ethnicity) | | Gender | Male, Female | **Media Slider:** - **Video on Slayder:** - **Video on Slayder:** **Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1QE22lSNq1i2xD5Gp-zEreWW_ZQ4ZPMcF) ### Technical Specifications **Table with data:** | Characteristic | Data | | --- | --- | | Video extension | MP4, MOV | **Source and data collection methodology:** Source and collection methodology: Data was collected via crowdsourcing platforms. ### Dataset Use Cases - Slider **Industry Cards:** - **Industry:** Financial Services & Digital Banking — **Title:** Strengthening Biometric Authentication Against Replay Attacks — **Text:** This anti-spoofing replay dataset supports banks and fintech platforms in training biometric authentication systems to detect replay attacks captured on mobile phones. The dataset contains real video recordings with facial features and presentation attacks, enabling accurate liveness detection, spoofing detection, and stronger biometric security during remote onboarding and identity verification. - **Industry:** Mobile Identity & Access Management — **Title:** Improving Face Recognition Security on Mobile Devices — **Text:** For mobile authentication providers, this anti-spoofing phone videos dataset helps refine face recognition and anti-spoofing algorithms under real-world conditions. By covering spoofing techniques such as replay attacks and printed photo attempts, it improves recognition systems designed to identify fake users and reduce fraud across mobile devices. - **Industry:** Government & Border Control Systems — **Title:** Reliable Face Antispoofing for Identity Verification — **Text:** Public sector identity systems use this biometric anti-spoofing dataset to enhance presentation attack detection in facial recognition workflows. The diverse video clips support training data for detecting spoofing attempts, ensuring secure identity checks in e-government services, digital IDs, and controlled-access environments. - **Industry:** AI Security & Computer Vision Research — **Title:** Training Robust Anti-Spoofing Detection Models — **Text:** Researchers and solution developers rely on this anti-spoofing dataset to benchmark detection systems and develop effective anti-spoofing solutions. With annotated video recordings from mobile phones, the dataset enables testing of spoofing attacks, replay detection, and deepfake detection methods for next-generation biometric security technologies. ### Fact **FAQs Heading:** FAQs **List of Questions:** - **Question:** What types of annotations are provided in this dataset? — **Answer:** The dataset includes technical metadata such as age, gender, and ethnicity. These annotations support demographic analysis and model evaluation without exposing sensitive personal information. - **Question:** What video formats and technical characteristics are available? — **Answer:** All video recordings are provided in MP4 and MOV formats. The dataset is optimized for use in biometric systems, recognition algorithms, and anti-spoofing detection pipelines. - **Question:** Why use phone-recorded videos instead of studio-recorded videos for anti-spoofing training? — **Answer:** Phone-recorded videos capture the real-world lighting, camera quality, and handling variation that biometric systems actually encounter in production, since most authentication happens through mobile apps. This dataset was collected via crowdsourcing on mobile devices specifically to reflect those real-world conditions rather than controlled studio settings. - **Question:** Can I request a sample of the anti-spoofing dataset before purchasing? — **Answer:** Yes. You can request a sample to evaluate video quality, metadata structure, and suitability for anti-spoofing algorithms. Sample data helps validate performance for face recognition, replay attack detection, and biometric authentication systems. - **Question:** How was the anti-spoofing replay data collected? — **Answer:** Data was collected via crowdsourcing platforms using mobile phone cameras. This approach ensures diverse recording conditions and realistic replay attack scenarios for training detection systems. - **Question:** How are Unidata datasets licensed? — **Answer:** Unidata follows a dual-licensing model. Free samples are available for testing and evaluation, while full anti-spoofing datasets are accessible exclusively through purchase. - **Question:** Do Unidata datasets comply with GDPR and data privacy regulations? — **Answer:** Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is collected from legally permissible sources to ensure ethical use in biometric security and research. - **Question:** How are Unidata datasets stored and secured? — **Answer:** All datasets are stored on AWS cloud infrastructure with security controls aligned to ISO 27001 and ISO 27701 standards. This ensures secure access, scalability, and privacy-focused data management. - **Question:** How long does it take to receive the dataset after purchase? — **Answer:** After submitting a request, Unidata reviews the requirements and completes documentation. Once agreements and payment are finalized, the dataset is delivered within 3–10 days. [Full list of this site's AI-readable pages](https://unidata.pro/llms.txt)