2022 CVPR CVPR 2022

Few-Shot Head Swapping in the Wild

Abstract

The head swapping task aims at flawlessly placing a source head onto a target body, which is of great importance to various entertainment scenarios. While face swapping has drawn much attention in the community, the task of head swapping has rarely been explored, particularly under the few-shot setting. It is inherently challenging due to its unique needs in head modeling and background blending. In this paper, we present the Head Swapper (HeSer), which achieves few-shot head swapping in the wild through two dedicated designed modules. Firstly, a Head2Head Aligner is devised to holistically migrate position and expression information from the target to the source head by examining multi-scale information. Secondly, to tackle the challenges of skin color variations and head-background mismatches, a Head2Scene Blender is introduced to simultaneously modify facial skin color and fill mismatched gaps on the background around the head. Particularly, seamless blending is achieved through a semantic-guided exemplar warping procedure. User studies and experimental results demonstrate that the proposed method produces superior head swapping results on a variety of scenes.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Vision and Deep Learning
🧭 Keyword Pioneer — head swapping
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio