title: GHOST 2.0: generative high-fidelity one shot transfer of heads
summary: While the task of face swapping has recently gained attention in the research
  community, a related problem of head swapping remains largely unexplored. In
  addition to skin color transfer, head swap poses extra challenges, such as the
  need to preserve structural information of the whole head during synthesis and
  inpaint gaps between swapped head and background. In this paper, we address
  these concerns with GHOST 2.0, which consists of two problem-specific modules.
  First, we introduce enhanced Aligner model for head reenactment, which
  preserves identity information at multiple scales and is robust to extreme pose
  variations. Secondly, we use a Blender module that seamlessly integrates the
  reenacted head into the target background by transferring skin color and
  inpainting mismatched regions. Both modules outperform the baselines on the
  corresponding tasks, allowing to achieve state of the art results in head
  swapping. We also tackle complex cases, such as large difference in hair styles
  of source and target. Code is available at
  https://github.com/ai-forever/ghost-2.0
paper_authors._id: 67c02b2eb14cf3cbc800c292
paper_authors.name: Alexander Groshev
paper_authors._id: 67c02b2eb14cf3cbc800c293
paper_authors.name: Anastasiia Iashchenko
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-27T09:13:49.896Z
paper_authors._id: 67aafccd7517c92ba71142f2
paper_authors.avatarUrl: /avatars/ef4b5c6867250b8b7af2c995dd7ad740.svg
paper_authors.fullname: Anastasiia Iashchenko
paper_authors.type: user
paper_authors.user: nastasia-y
paper_authors._id: 67c02b2eb14cf3cbc800c294
paper_authors.name: Pavel Paramonov
paper_authors._id: 67c02b2eb14cf3cbc800c295
paper_authors.name: Denis Dimitrov
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-27T12:54:35.272Z
paper_authors._id: 6669a678465d1d802181e456
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/6669a678465d1d802181e456/ZCthBBhDFQnh0bBkgUQUU.png
paper_authors.fullname: Denis Dimitrov
paper_authors.type: user
paper_authors.user: dendimitrov
paper_authors._id: 67c02b2eb14cf3cbc800c296
paper_authors.name: Andrey Kuznetsov
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-27T12:54:37.211Z
paper_authors._id: 643984dceb7c5616ef3f5d54
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/643984dceb7c5616ef3f5d54/10JRkblrRIEVci6UJwvPz.jpeg
paper_authors.fullname: Andrey Kuznetsov
paper_authors.type: user
paper_authors.user: kuznetsoffandrey
paper_title: GHOST 2.0: generative high-fidelity one shot transfer of heads
paper_summary: While the task of face swapping has recently gained attention in the research
  community, a related problem of head swapping remains largely unexplored. In
  addition to skin color transfer, head swap poses extra challenges, such as the
  need to preserve structural information of the whole head during synthesis and
  inpaint gaps between swapped head and background. In this paper, we address
  these concerns with GHOST 2.0, which consists of two problem-specific modules.
  First, we introduce enhanced Aligner model for head reenactment, which
  preserves identity information at multiple scales and is robust to extreme pose
  variations. Secondly, we use a Blender module that seamlessly integrates the
  reenacted head into the target background by transferring skin color and
  inpainting mismatched regions. Both modules outperform the baselines on the
  corresponding tasks, allowing to achieve state of the art results in head
  swapping. We also tackle complex cases, such as large difference in hair styles
  of source and target. Code is available at
  https://github.com/ai-forever/ghost-2.0
paper_ai_summary: GHOST 2.0, consisting of an Aligner and Blender module, achieves state-of-the-art results in head swapping by preserving identity information, handling extreme poses, and seamlessly integrating the reenacted head into the target background.
paper_ai_keywords: Aligner Blender head reenactment skin color transfer inpainting identity information extreme pose variations