Datasets:
Tasks:
Video Classification
Modalities:
Video
Size:
< 1K
Tags:
ibeta-level-1
ibeta-certification
face-anti-spoofing
face-liveness-detection
liveness-detection
presentation-attack-detection
License:
| license: cc-by-4.0 | |
| tags: | |
| - ibeta-level-1 | |
| - ibeta-certification | |
| - face-anti-spoofing | |
| - face-liveness-detection | |
| - liveness-detection | |
| - presentation-attack-detection | |
| - pad | |
| - biometrics | |
| - face-recognition | |
| - spoofing | |
| - anti-spoofing | |
| - paper-attack | |
| - print-attack | |
| - cutout-attack | |
| - eyeholes-mask | |
| - cylinder-paper-mask | |
| - replay-attack | |
| - smartphone-replay | |
| - display-replay | |
| - iso-30107-3 | |
| - ekyc | |
| - identity-verification | |
| - biometric-authentication | |
| task_categories: | |
| - video-classification | |
| # iBeta Level 1 Dataset for Face Anti-Spoofing & Liveness Detection | |
| A presentation attack dataset for iBeta Level 1 PAD certification preparation, built for **face anti-spoofing**, **liveness detection**, and **biometric face recognition** systems. The dataset contains **30,000+ attack videos** covering all major Level 1 attack vectors: printed photo attacks, cutout paper masks, eyeholes masks, cylinder paper masks, photo masks worn by actors, and display-based replay | |
| attacks | |
|  | |
| ## What Is iBeta Level 1? | |
| iBeta Level 1 is the entry-level PAD certification tier from iBeta Quality Assurance, an independent NIST-NVLAP-accredited testing laboratory. Level 1 testing evaluates whether face recognition systems can defeat the most common 2D presentation attacks: paper prints, cutouts, eyeholes masks, and basic display replays. iBeta Level 1 compliance is increasingly required for biometric authentication systems deployed in eKYC, fintech onboarding, banking, and identity verification | |
| ## Dataset Description | |
| The dataset combines two attack categories with separate participant | |
| pools: | |
| - **Paper-based attacks**: 22,000+ videos from 85+ participants | |
| - **Replay attacks**: 8,000+ videos from 2,500+ selfie contributors | |
| Total: **30,000+ presentation attack videos** designed for end-to-end face anti-spoofing model training and iBeta Level 1 PAD certification preparation | |
| ## Key Features | |
| - **22,000+ Paper Mask Attacks** including print, cutout, eyeholes, cylinder-based volume effects, and 3D paper masks with structural elements (e.g., nose) | |
| - **8,000+ Replay Clips** with photos and videos replayed on smartphone (iOS/Android) and desktop monitor displays under varying brightness, distances, and angles | |
| - **Active Liveness Sequences** - zoom-in and zoom-out phases to evaluate motion-based liveness detection | |
| - **Multi-Ethnic Demographics** - balanced representation of Caucasian, Black, and Asian participants | |
| - **Multi-Device Capture** - iOS and Android phones (multiple device models) | |
| ## Full version of the dataset is available for commercial usage. Leave a request on our website [Axonlabs](https://axonlabs.pro/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to purchase the dataset 💰 | |
| ## For feedback and additional sample requests, please [contact us](https://axonlab.ai/dataset/ibeta-level-1-dataset/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link)! | |
| ## Attack Type Variations | |
| This dataset provides comprehensive coverage of iBeta Level 1 attack scenarios: | |
| - **Print and cutout paper attacks** - flat printed photos and cutouts shaped to face contours | |
| - **Cylinder paper masks** - printed photos shaped into cylinders to create volume effects | |
| - **3D paper masks** with structural facial elements (nose, etc.) | |
| - **Photo masks worn by actors** with head and eye variations | |
| - **Smartphone replay attacks** - photos/videos replayed on iOS and Android phone screens | |
| - **Monitor/laptop replay attacks** - photos/videos replayed on desktop displays | |
| ## Potential Use Cases | |
| - **iBeta Level 1 certification preparation** - train face anti-spoofing models against all L1 attack vectors before formal testing | |
| - **APCER/BPCER threshold validation** - measure Attack Presentation Classification Error Rate and Bona fide Presentation Classification Error Rate under ISO/IEC 30107-3 | |
| - **Face recognition spoof robustness testing** - evaluate production face recognition systems against paper and replay attacks | |
| - **eKYC and identity verification** - prepare biometric authentication systems for fintech and banking deployment | |
| - **Cross-attack generalization research** - analyze model performance across paper vs replay attack categories | |
| ## Academic Reference | |
| The canonical academic benchmarks for iBeta Level 1 attack vectors are the **Idiap Print-Attack Database** and **Idiap Replay-Attack Database** - foundational datasets from the Idiap Research Institute. This commercial dataset extends those research lines with significantly more participants (2,500+ vs Idiap's 50), modern smartphone capture, broader demographics, and direct iBeta certification mapping | |
| ## Related Datasets by Axon Labs | |
| - [iBeta Level 2 Certification Dataset](https://huggingface.co/datasets/AxonData/iBeta-Level-2-Certification-Dataset) - 25,000+ videos for advanced 3D mask attacks (L2) | |
| - [iBeta Level 3 Dataset](https://huggingface.co/datasets/AxonData/ibeta-level-3-dataset) - high-fidelity rubber and resin masks for the strictest L3 testing | |
| - [Photo Print Attack Dataset](https://huggingface.co/datasets/AxonData/Anti_spoofing_dataset_Print_attack) - focused 2D photo print attacks | |
| - [Display Replay Attacks Dataset](https://huggingface.co/datasets/AxonData/Display_replay_attacks) - display-based replay attacks | |
| - [Liveness Detection Dataset](https://huggingface.co/datasets/AxonData/liveness-detection-dataset) - comprehensive 11+ attack types in one dataset | |
| ## About Axon Labs | |
| Axon Labs builds biometric AI training datasets. We specialize in face liveness detection, face recognition, and voice anti-spoofing data for production identity verification, eKYC, fintech, and government applications | |
| ## Commercial Access | |
| Sample subset publicly available for evaluation. For full commercial dataset access, pricing, and licensing terms, contact [sales@axonlabs.pro](mailto:sales@axonlabs.pro) or visit [axonlab.ai](https://axonlab.ai/). | |
| ## Contact and Feedback | |
| We welcome your feedback! Feel free to reach out to us and share your experience with this dataset. If you're interested, you can also **receive additional samples for free**! 😊 | |
| Visit us at [**Axonlabs**](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to request a full version of the dataset for commercial usage. |