The dataset contains around 9.6k images of human faces which are both real images and those generated by AI.

The zip contains two folders: - Real Images: 5000 images of real human faces - AI-Generated Images: 4630 images of ai-generated human faces.

The BioID Face Database has been recorded and is published to give all researchers working in the area of face detection the possibility to compare the quality of their face detection algorithms with others. During the recording special emphasis has been laid on real world conditions. Therefore the testset features a large variety of illumination, background and face size. The dataset consists of 1521 gray level images with a resolution of 384x286 pixel. Each one shows the frontal view of a face of one out of 23 different test persons. For comparison reasons the set also contains manually set eye postions. The images are labeled BioID_xxxx.pgm where the characters xxxx are replaced by the index of the current image (with leading zeros). Similar to this, the files BioID_xxxx.eye contain the eye positions for the corresponding images.

Image Dataset of face images for compuer vision tasks

Dataset comprises 500,600+ images of individuals representing various races, genders, and ages, with each person having a single face image. It is designed for facial recognition and face detection research, supporting the development of advanced recognition systems. By leveraging this dataset, researchers and developers can enhance deep learning models, improve face verification and face identification techniques, and refine… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/face-recognition-image-dataset.

The Tufts Face Database is a comprehensive collection of human face images, ideal for facial recognition, biometric verification, and computer vision model training. It includes diverse data by ethnicity, age, gender, and region for robust AI development.

FGnet Markup Scheme of the BioID Face Database - The BioID Face Database is being used within the FGnet project of the European Working Group on face and gesture recognition. David Cristinacce and Kola Babalola, PhD students from the department of Imaging Science and Biomedical Engineering at the University of Manchester marked up the images from the BioID Face Database. They selected several additional feature points, which are very useful for facial analysis and gesture recognition.

Face Recognition, Face Detection, Male Photo Dataset 👨

The dataset is created on the basis of Selfies and ID Dataset

110,000+ photos of 74,000+ men from 141 countries. The dataset includes photos of people's faces. All people presented in the dataset are men. The dataset contains a variety of images capturing individuals from diverse backgrounds and age groups.

Our dataset will diversify your data by adding more photos of men of different ages and ethnic groups, enhancing the quality of your model.

People in the dataset https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F4b36d906144803b5f4b1fb6bbb17246c%2FFrame%20109.png?generation=1714650925000102&alt=media" alt="">

The dataset can be utilized for a wide range of tasks, including face recognition, age estimation, image feature extraction, or any problem related to human image analysis.

👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 95,000+ human images & videos - Full dataset

Metadata for the dataset:

• id - unique identifier of the media file
• photo - link to access the photo,
• age - age of the person
• country - country of the person
• ethnicity - ethnicity of the person
• photo_extension - photo extension,
• photo_resolution - photo resolution

Statistics for the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fc7e8e8029a7e65e7f6f2ccc53e1b6f5d%2FMale%20Images.png?generation=1714650553018057&alt=media" alt="">

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Content

The dataset consists of: - files - includes 20 images corresponding to each person in the sample, - .csv file - contains information about the images and people in the dataset

File with the extension .csv

• id: id of the person,
• age - age of the person,
• country - country of the person,
• ethnicity - ethnicity of the person,
• photo_extension: extension of the photo,
• photo_resolution: photo_resolution of the photo

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keywords: biometric system, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human faces dataset, machine learning, image-to-image, verification models, digital photo-identification, men images, males dataset, male selfie, male face recognition

Dataset of face images with different angles and head positions

Dataset contains 23,110 individuals, each contributing 28 images featuring various angles and head positions, diverse backgrounds, and attributes, along with 1 ID photo. In total, the dataset comprises over 670,000 images in formats such as JPG and PNG. It is designed to advance face recognition and facial recognition research, focusing on person re-identification and recognition systems.

By utilizing this dataset, researchers can explore various recognition applications, including face verification, face identification. - Get the data

Metadata for the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Fed374cc92b935b209749cb7b32fd41da%2FFrame%201%20(10).png?generation=1743160276352983&alt=media" alt=""> The accuracy of labels of face pose is more than 97%, ensuring reliable data for training and testing recognition algorithms.

💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.

Dataset includes high-quality images that capture human faces in different poses and expressions, allowing for comprehensive analysis in recognition tasks. It is particularly valuable for developing and evaluating deep learning models and computer vision techniques.

🌐 UniData provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects

This dataset is a curated subset of 3000 images extracted from a larger collection of approximately 80,000 AI-generated faces. It features diverse, synthetic facial images created using advanced generative models, each with unique characteristics and expressions. Designed for focused testing and smaller-scale machine learning tasks, this subset offers a manageable sample size for experimentation with facial recognition and model validation. For broader applications and comprehensive studies, refer to the full dataset available at Original Dataset.

To access images in the ai-face-dataset-3000-images directory on Kaggle, list the files using os.listdir('/kaggle/input/ai-face-dataset-3000-images'). You can then load and process an image using libraries like PIL with Image.open('/kaggle/input/ai-face-dataset-3000-images/your-image-file.jpg').

Introduction

Welcome to the Middle Eastern Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

Facial Image Data

The dataset comprises over 3,000 high-quality facial images, organized into participant-wise sets. Each set includes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure robustness and real-world utility, images were captured under diverse conditions:

Metadata

Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

This rich metadata helps train models that can recognize faces even when partially obscured.

Use Cases & Applications

This dataset is ideal for a wide range of real-world and research-focused applications, including:

Secure & Ethical Collection

Dataset

Includes face images of 11 subjects with 3 sets of images: one of the subject with no occlusion, one of them wearing a hat, and one of them wearing glasses. Each set consists of 5 subject positions (subject's two profile positions, one central position, and two positions angled between the profile and central positions), with 7 lighting angles for each position (completing a 180 degree arc around the subject), and 5 light settings for each angle (warm, cold, low, medium, and bright). Images are 5184 pixels tall by 3456 pixels wide and are saved in .JPG format.

The dataset consists of images capturing people displaying 7 distinct emotions (anger, contempt, disgust, fear, happiness, sadness and surprise). Each image in the dataset represents one of these specific emotions, enabling researchers and machine learning practitioners to study and develop models for emotion recognition and analysis. The images encompass a diverse range of individuals, including different genders, ethnicities, and age groups*. The dataset aims to provide a comprehensive representation of human emotions, allowing for a wide range of use cases.

Introduction

Welcome to the East Asian Multi-Year Facial Image Dataset, thoughtfully curated to support the development of advanced facial recognition systems, biometric identification models, KYC verification tools, and other computer vision applications. This dataset is ideal for training AI models to recognize individuals over time, track facial changes, and enhance age progression capabilities.

Facial Image Data

This dataset includes over 10,000+ high-quality facial images, organized into individual participant sets, each containing:

Diversity & Representation

Image Quality & Capture Conditions

To ensure model generalization and practical usability, images in this dataset reflect real-world diversity:

Metadata

Each participant’s dataset is accompanied by rich metadata to support advanced model training and analysis, including:

Use Cases & Applications

This dataset is highly valuable for a wide range of AI and computer vision applications:

Secure & Ethical Collection

Dataset Updates & Customization

To keep pace with evolving AI needs, this dataset is regularly updated and customizable. Custom data collection options include:

Face Detection - Object Detection & Face Recognition Dataset

The dataset is created on the basis of Selfies and ID Dataset

The dataset is a collection of images (selfies) of people and bounding box labeling for their faces. It has been specifically curated for face detection and face recognition tasks. The dataset encompasses diverse demographics, age, ethnicities, and genders.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F01348572e2ae2836f10bc2f2da381009%2FFrame%2050%20(1).png?generation=1699439342545305&alt=media" alt="">

The dataset is a valuable resource for researchers, developers, and organizations working on age prediction and face recognition to train, evaluate, and fine-tune AI models for real-world applications. It can be applied in various domains like psychology, market research, and personalized advertising.

👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 95,000+ human images & videos - Full dataset

Metadata for the full dataset:

• assignment_id - unique identifier of the media file
• 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
• photo_1_extension, photo_2_extension, …, photo_15_extension - photo extensions in the dataset
• photo_1_resolution, photo_2_resolution, …, photo_15_resolution - photo resolution in the dataset

OTHER BIOMETRIC DATASETS:

• Anti Spoofing Real Dataset
• Antispoofing Replay Dataset
• Selfies, ID Images dataset (5591 sets of 15 files)
• Selfies and video dataset (4 052 sets)
• Dataset of bald people, 5000 images

🧩 This is just an example of the data. Leave a request here to learn more

Dataset structure

• images - contains of original images of people
• labels - includes visualized labeling for the original images
• annotations.xml - contains coordinates of the bbox, created for the original photo

Data Format

Each image from images folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the polygons and labels . For each point, the x and y coordinates are provided.

Example of XML file structure

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F19e61b2d0780e9db80afe4a0ce879c4b%2Fcarbon.png?generation=1699440100527867&alt=media" alt="">

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keywords: biometric system, biometric system attacks, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human faces dataset

Similar face recognition has always been one of the most challenging research directions in face recognition.This project shared similar face images (SFD.zip) that we have collected so far. All images are labeld and collected from publicly available datasets such as LFW, CASIA-WebFace.We will continue to collect larger-scale data and continue to update this project.Because the data set is too large, we uploaded a compressed zip file (SFD.zip). Meanwhile here we upload a few examples for everyone to view.email: ileven@shu.edu.cn

Introduction

Welcome to the South Asian Facial Expression Image Dataset, curated to support the development of advanced facial expression recognition systems, biometric identification models, KYC verification processes, and a wide range of facial analysis applications. This dataset is ideal for training robust emotion-aware AI solutions.

Facial Expression Data

The dataset includes over 2000 high-quality facial expression images, grouped into participant-wise sets. Each participant contributes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure generalizability and robustness in model training, images were captured under varied real-world conditions:

Metadata

Each participant's image set is accompanied by detailed metadata, enabling precise filtering and training:

This metadata helps in building expression recognition models that are both accurate and inclusive.

Use Cases & Applications

This dataset is ideal for a variety of AI and computer vision applications, including:

Secure & Ethical Collection

Dataset Updates & Customization

To support evolving AI development needs, this dataset is regularly updated and can be tailored to project-specific requirements. Custom options include:

SCface is a database of static images of human faces. Images were taken in uncontrolled indoor environment using five video surveillance cameras of various qualities. Database contains 4160 static images (in visible and infrared spectrum) of 130 subjects. Images from different quality cameras mimic the real-world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios.

The Pgu-Face dataset contains 896 images from 224 different subjects. All of the subjects was Iranian men and most of them live in tropical regions of the southwest of Iran. The range of age of the subject's was 16 to 82 years with average 27.89 years. In addition, we make the following information available for the subjects: age and quality of the camera in mega pixels.

Emotion recognition Dataset

Dataset comprises 199,955 images featuring 28,565 individuals displaying a variety of facial expressions. It is designed for research in emotion recognition and facial expression analysis across diverse races, genders, and ages. By utilizing this dataset, researchers and developers can enhance their understanding of facial recognition technology and improve the accuracy of emotion classification systems. - Get the data This dataset includes images that… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/facial-expression-recognition-dataset.

Perception of facial identity and emotional expressions is fundamental to social interactions. Recently, interest in age associated changes in the processing of faces has grown rapidly. Due to the lack of older faces stimuli, most previous age-comparative studies only used young faces stimuli, which might cause own-age advantage. None of the existing Eastern face stimuli databases contain face images of different age groups (e.g. older adult faces). In this study, a database that comprises images of 110 Chinese young and older adults displaying eight facial emotional expressions (Neutral, Happiness, Anger, Disgust, Surprise, Fear, Content, and Sadness) was constructed. To validate this database, each image was rated on the basis of perceived facial expressions, perceived emotional intensity, and perceived age by two different age groups. Results have shown an overall 79.08% correct identification rate in the validation. Access to the freely available database can be requested by emailing the corresponding authors.

Images are of 102 adult faces 1350x1350 pixels in full colour. Template files mark out 189 coordinates delineating face shape, for use with Psychomorph or WebMorph.org.Self-reported age, gender and ethnicity are included in the file london_faces_info.csv. Attractiveness ratings (on a 1-7 scale from "much less attractiveness than average" to "much more attractive than average") for the neutral front faces from 2513 people (ages 17-90) are included in the file london_faces_ratings.csv.All individuals gave signed consent for their images to be "used in lab-based and web-based studies in their original or altered forms and to illustrate research (e.g., in scientific journals, news media or presentations)." Images were taken in London, UK, in April 2012.