AFLW2000-3D is a dataset of 2000 images that have been annotated with image-level 68-point 3D facial landmarks. This dataset is used for evaluation of 3D facial landmark detection models. The head poses are very diverse and often hard to be detected by a CNN-based face detector.
98 PAPERS • 8 BENCHMARKS
FaceWarehouse is a 3D facial expression database that provides the facial geometry of 150 subjects, covering a wide range of ages and ethnic backgrounds.
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FaceScape dataset provides 3D face models, parametric models and multi-view images in large-scale and high-quality. The camera parameters, the age and gender of the subjects are also included. The data have been released to public for non-commercial research purpose.
28 PAPERS • NO BENCHMARKS YET
Curates a dataset of SMPL-X fits on in-the-wild images.
19 PAPERS • NO BENCHMARKS YET
The goal of this benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods under variations in viewing angle, lighting, and common occlusions.
18 PAPERS • 1 BENCHMARK
The REALY benchmark aims to introduce a region-aware evaluation pipeline to measure the fine-grained normalized mean square error (NMSE) of 3D face reconstruction methods from under-controlled image sets.
14 PAPERS • 2 BENCHMARKS
This is a gun detection dataset with 51K annotated gun images for gun detection and other 51K cropped gun chip images for gun classification collected from a few different sources.
5 PAPERS • 4 BENCHMARKS
FFHQ-UV is a large-scale facial UV-texture dataset that contains over 50,000 high-quality texture UV-maps with even illuminations, neutral expressions, and cleaned facial regions, which are desired characteristics for rendering realistic 3D face models under different lighting conditions. The dataset is derived from FFHQ and preserves the most variations in FFHQ.
1 PAPER • NO BENCHMARKS YET
Description: 1,056 People Living_face & Anti-Spoofing Data. The collection scenes include indoor and outdoor scenes. The data includes male and female. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The data includes multiple postures, multiple expressions, and multiple anti-spoofing samples. The data can be used for tasks such as face payment, remote ID authentication, and face unlocking of mobile phone.
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Description: 5,199 People – 3D Face Recognition Images Data. The collection scene is indoor scene. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes multiple facial postures, multiple light conditions, multiple indoor scenes. This data can be used for tasks such as 3D face recognition.
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