CVGRApr 27, 2022

Few-Shot Head Swapping in the Wild

arXiv:2204.13100v130 citationsh-index: 60
Originality Incremental advance
AI Analysis

This addresses head swapping for entertainment applications, but it is incremental as it builds on face swapping with a novel focus on head modeling and background blending.

The paper tackles the problem of few-shot head swapping in the wild by proposing the Head Swapper (HeSer) with modules for aligning pose and expression and blending skin color and background, achieving superior results in various scenes.

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, 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 delicately designed modules. Firstly, a Head2Head Aligner is devised to holistically migrate pose 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 in the swapping procedure, a Head2Scene Blender is introduced to simultaneously modify facial skin color and fill mismatched gaps in the background around the head. Particularly, seamless blending is achieved with the help of a Semantic-Guided Color Reference Creation procedure and a Blending UNet. Extensive experiments demonstrate that the proposed method produces superior head swapping results in a variety of scenes.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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