Photoswap: Personalized Subject Swapping in Images
In an era where images and visual content dominate our digital landscape, the
ability to manipulate and personalize these images has become a necessity.
Envision seamlessly substituting a tabby cat lounging on a sunlit window sill
in a photograph with your own playful puppy, all while preserving the original
charm and composition of the image. We present Photoswap, a novel approach that
enables this immersive image editing experience through personalized subject
swapping in existing images. Photoswap first learns the visual concept of the
subject from reference images and then swaps it into the target image using
pre-trained diffusion models in a training-free manner. We establish that a
well-conceptualized visual subject can be seamlessly transferred to any image
with appropriate self-attention and cross-attention manipulation, maintaining
the pose of the swapped subject and the overall coherence of the image.
Comprehensive experiments underscore the efficacy and controllability of
Photoswap in personalized subject swapping. Furthermore, Photoswap
significantly outperforms baseline methods in human ratings across subject
swapping, background preservation, and overall quality, revealing its vast
application potential, from entertainment to professional editing.
64756ca0a51711a3b5915bcb
Jing Gu
claimed_verified
2023-05-30T09:10:49.371Z
634781fae5c0717e6739bc59
/avatars/2b6d2d0625741b28f326459acad55b69.svg
Jing Gu
user
jinggu
64756ca0a51711a3b5915bcc
Yilin Wang
64756ca0a51711a3b5915bcd
Nanxuan Zhao
64756ca0a51711a3b5915bce
Tsu-Jui Fu
64756ca0a51711a3b5915bcf
Wei Xiong
64756ca0a51711a3b5915bd0
Qing Liu
64756ca0a51711a3b5915bd1
Zhifei Zhang
64756ca0a51711a3b5915bd2
He Zhang
64756ca0a51711a3b5915bd3
Jianming Zhang
64756ca0a51711a3b5915bd4
HyunJoon Jung
64756ca0a51711a3b5915bd5
Xin Eric Wang
claimed_verified
2024-04-09T18:39:16.496Z
64679a226192d39142245e5e
/avatars/05abee0b6317f100923936ca2099e9eb.svg
Xin Eric Wang
user
xw-eric
Photoswap: Personalized Subject Swapping in Images
In an era where images and visual content dominate our digital landscape, the
ability to manipulate and personalize these images has become a necessity.
Envision seamlessly substituting a tabby cat lounging on a sunlit window sill
in a photograph with your own playful puppy, all while preserving the original
charm and composition of the image. We present Photoswap, a novel approach that
enables this immersive image editing experience through personalized subject
swapping in existing images. Photoswap first learns the visual concept of the
subject from reference images and then swaps it into the target image using
pre-trained diffusion models in a training-free manner. We establish that a
well-conceptualized visual subject can be seamlessly transferred to any image
with appropriate self-attention and cross-attention manipulation, maintaining
the pose of the swapped subject and the overall coherence of the image.
Comprehensive experiments underscore the efficacy and controllability of
Photoswap in personalized subject swapping. Furthermore, Photoswap
significantly outperforms baseline methods in human ratings across subject
swapping, background preservation, and overall quality, revealing its vast
application potential, from entertainment to professional editing.
Photoswap enables seamless subject swapping in images using pre-trained diffusion models with self-attention and cross-attention manipulation, preserving pose and coherence.
diffusion models self-attention cross-attention