datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
face-anti-spoofing-dataset
Face Antispoofing dataset for liveness detection
Anti-Spoofing dataset: live, replay, cut, print, 3D masks - large-scale face anti spoofing
This dataset delivers a single, end-to-end resource for training and benchmarking facial liveness-detection systems. By aggregating live sessions and eleven realistic presentation-attack classes into one collection, it accelerates development toward iBeta Level 1/2 compliance and strengthens model robustness against the full spectrum of spoofing… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/face-anti-spoofing-dataset.face-anti-spoofing
Face Antispoofing dataset for recognition systems
The dataset consists of 98,000 videos and selfies from 170 countries, providing a foundation for developing robust security systems and facial recognition algorithms.
While the dataset itself doesn't contain spoofing attacks, it's a valuable resource for testing liveness detection system, allowing researchers to simulate attacks and evaluate how effectively their systems can distinguish between real faces and various forms of… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/face-anti-spoofing.312-People-3D-Living_Face-Anti_Spoofing-Data
Description
312명 규모의 3D 안면 안티 스푸핑 데이터셋으로, 실내 및 실외 환경에서 수집된 데이터를 포함합니다. 남성과 여성 모두 포함하며, 연령은 아동부터 고령층까지 다양한 범위로 구성되어 있고 청년층과 중년층이 주를 이룹니다. 데이터 수집에는 iPhone X와 iPhone XR을 사용했습니다. 다양한 표정, 얼굴 자세, 안티 스푸핑 샘플, 다양한 조명 조건 및 다양한 환경을 포함하여 데이터의 다양성을 확보했습니다. 본 데이터셋은 3D 얼굴 인식, 3D Living Face 및 안면 안티 스푸핑 등의 작업에 활용할 수 있습니다.
자세한 내용은 아래 링크를 참고해 주세요: https://ko.nexdata.ai/datasets/computervision/1089?source=hf.kr
Data size
312명, 1인당 168장의 이미지
Population distribution
인종… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-kr/312-People-3D-Living_Face-Anti_Spoofing-Data.face-anti-spoofing-dataset
Face Antispoofing dataset for liveness detection
Anti-Spoofing dataset: live, replay, cut, print, 3D masks - large-scale face anti spoofing
This dataset delivers a single, end-to-end resource for training and benchmarking facial liveness-detection systems. By aggregating live sessions and eleven realistic presentation-attack classes into one collection, it accelerates development toward iBeta Level 1/2 compliance and strengthens model robustness against the full spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/helloleandronascimento/face-anti-spoofing-dataset.Face-Spoofing-in-the-Wild-Multi-Mask
Liveness Detection Dataset in the Wild with High Variety
Spoof in the Wild Dataset
Dataset for PAD/liveness detection with three classes of presentation attacks: cardboard masks with cut-out eyes; elastic textile mesh masks with full-color face printing; full-size latex 3D masks. Mask types were selected based on real-world attack scenarios
The key value is high variety:
different actors, a large number of individual masks, various lighting (indoor/outdoor… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/Face-Spoofing-in-the-Wild-Multi-Mask.face-anti-spoofing-dataset
Face Antispoofing dataset for liveness detection
Anti-Spoofing dataset: live, replay, cut, print, 3D masks - large-scale face anti spoofing
This dataset delivers a single, end-to-end resource for training and benchmarking facial liveness-detection systems. By aggregating live sessions and eleven realistic presentation-attack classes into one collection, it accelerates development toward iBeta Level 1/2 compliance and strengthens model robustness against the full spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/marcusmball/face-anti-spoofing-dataset.