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The 828 sets of video face-swapping data each contain one face image, one original video, and one face-swapped video.Replace the face in the original video with the face from the image using the tool at https://www.picsi .Face swapping is performed only between faces with the same skin tone. After face swapping, the video shows a high degree of facial fit, and the inter-frame facial similarity in the face-swapped video reaches over 97% . The data cover men, women, White people, Black people, Southeast Asians, etc. It includes multiple languages, speech content on multiple topics, a mix of landscape and portrait orientations, multiple backgrounds, and multiple age groups. In the images or videos, the subjects simulate a video conference scenario, look straight into the camera, and are shown from the waist/chest up. The data can be used for application scenarios such as cross-racial face recognition, liveness detection, digital humans, video face swapping, and face forgery detection.
This is a paid dataset licensed for commercial use. Ready-made datasets are available for immediate integration into AI projects.
Specifications
Data content
A data group consists of one image, one original video, and one face-swapped video (Replace the face in the original video with the face from the image using the tool at https://www.picsi.ai/en/app). Each image contains only one face, and each video contains only one face. The image is taken from a frame in the video. In each data group, the face in the image and the face in the original video are not the same person.
Data scale
828 groups.
Gender distribution
male, female.
Skin-color distribution
White people, Black people, Southeast Asians, etc.
Original video capture environment
indoor.
Original video capture devices
smartphones, webcams (built-in laptop cameras or external USB cameras).
Diversity of original video capture
multiple races/skin colors, multiple languages, speech content on multiple topics, mixed landscape and portrait orientations, multiple backgrounds, multiple age groups.
Data formats
mp4 video format; RGB image format.
Pixels
total image pixels range from 777,600 px to 8,294,400 px; video resolutions include 1280x720, 1920×1080, 3840×2160, etc.
Face-swapping criteria
face swapping is performed only between faces of the same skin color, i.e., the face in the image and the face in the original video in each data group belong to the same skin color. For example, Yellow-skinned (excluding Chinese) faces are swapped only with Yellow-skinned (excluding Chinese) faces, Black faces only with Black faces, and White faces only with White faces.
Metric
After face swapping, the video shows a high degree of facial fit, and the inter-frame facial similarity in the face-swapped video reaches over 97%.
What types of computer vision applications can Nexdata’s datasets support?
Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.
Can Nexdata customize Computer Vision datasets based on our specific requirements?
Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.
How does Nexdata ensure the quality and scalability of its Computer Vision datasets?
Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.
Specifications
Sample
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