title: VGGHeads: A Large-Scale Synthetic Dataset for 3D Human Heads
summary: Human head detection, keypoint estimation, and 3D head model fitting are
  important tasks with many applications. However, traditional real-world
  datasets often suffer from bias, privacy, and ethical concerns, and they have
  been recorded in laboratory environments, which makes it difficult for trained
  models to generalize. Here, we introduce VGGHeads -- a large scale synthetic
  dataset generated with diffusion models for human head detection and 3D mesh
  estimation. Our dataset comprises over 1 million high-resolution images, each
  annotated with detailed 3D head meshes, facial landmarks, and bounding boxes.
  Using this dataset we introduce a new model architecture capable of
  simultaneous heads detection and head meshes reconstruction from a single image
  in a single step. Through extensive experimental evaluations, we demonstrate
  that models trained on our synthetic data achieve strong performance on real
  images. Furthermore, the versatility of our dataset makes it applicable across
  a broad spectrum of tasks, offering a general and comprehensive representation
  of human heads. Additionally, we provide detailed information about the
  synthetic data generation pipeline, enabling it to be re-used for other tasks
  and domains.
paper_authors._id: 66b651ea429d671b41186638
paper_authors.name: Orest Kupyn
paper_authors._id: 66b651ea429d671b41186639
paper_authors.name: Eugene Khvedchenia
paper_authors._id: 66b651ea429d671b4118663a
paper_authors.name: Christian Rupprecht
paper_title: VGGHeads: A Large-Scale Synthetic Dataset for 3D Human Heads
paper_summary: Human head detection, keypoint estimation, and 3D head model fitting are
  important tasks with many applications. However, traditional real-world
  datasets often suffer from bias, privacy, and ethical concerns, and they have
  been recorded in laboratory environments, which makes it difficult for trained
  models to generalize. Here, we introduce VGGHeads -- a large scale synthetic
  dataset generated with diffusion models for human head detection and 3D mesh
  estimation. Our dataset comprises over 1 million high-resolution images, each
  annotated with detailed 3D head meshes, facial landmarks, and bounding boxes.
  Using this dataset we introduce a new model architecture capable of
  simultaneous heads detection and head meshes reconstruction from a single image
  in a single step. Through extensive experimental evaluations, we demonstrate
  that models trained on our synthetic data achieve strong performance on real
  images. Furthermore, the versatility of our dataset makes it applicable across
  a broad spectrum of tasks, offering a general and comprehensive representation
  of human heads. Additionally, we provide detailed information about the
  synthetic data generation pipeline, enabling it to be re-used for other tasks
  and domains.
paper_ai_keywords: diffusion models 3D head meshes facial landmarks bounding boxes heads detection head meshes reconstruction