Title
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, 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.
Year
Venue
DocType
2022
IEEE Conference on Computer Vision and Pattern Recognition
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
10
Name
Order
Citations
PageRank
Changyong Shu100.34
Hemao Wu200.34
Hang Zhou300.68
Jiaming Liu411.03
Zhibin Hong5374.94
Changxing Ding600.68
Junyu Han78511.12
jingtuo liu8479.43
Er-rui Ding914229.31
Jingdong Wang1000.34