Portrait Dataset

Portrait datasets are collections of facial images used to train and evaluate computer vision models, primarily focusing on tasks like face generation, 3D face reconstruction, and portrait matting. Current research emphasizes creating datasets with diverse poses, high resolution, and fine-grained annotations to improve the realism and accuracy of generated portraits, often employing generative adversarial networks (GANs) and diffusion models. These advancements are crucial for applications ranging from virtual avatars and video conferencing to enhancing image editing and privacy-preserving technologies.