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Main Authors: Xie, Cong, Zou, Han, Yu, Ruiqi, Zhang, Yan, Zhan, Zhenpeng
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.01485
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author Xie, Cong
Zou, Han
Yu, Ruiqi
Zhang, Yan
Zhan, Zhenpeng
author_facet Xie, Cong
Zou, Han
Yu, Ruiqi
Zhang, Yan
Zhan, Zhenpeng
contents In this work, we are interested in achieving both high text controllability and whole-body appearance consistency in the generation of personalized human characters. We propose a novel framework, named SerialGen, which is a serial generation method consisting of two stages: first, a standardization stage that standardizes reference images, and then a personalized generation stage based on the standardized reference. Furthermore, we introduce two modules aimed at enhancing the standardization process. Our experimental results validate the proposed framework's ability to produce personalized images that faithfully recover the reference image's whole-body appearance while accurately responding to a wide range of text prompts. Through thorough analysis, we highlight the critical contribution of the proposed serial generation method and standardization model, evidencing enhancements in appearance consistency between reference and output images and across serial outputs generated from diverse text prompts. The term "Serial" in this work carries a double meaning: it refers to the two-stage method and also underlines our ability to generate serial images with consistent appearance throughout.
format Preprint
id arxiv_https___arxiv_org_abs_2412_01485
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SerialGen: Personalized Image Generation by First Standardization Then Personalization
Xie, Cong
Zou, Han
Yu, Ruiqi
Zhang, Yan
Zhan, Zhenpeng
Computer Vision and Pattern Recognition
In this work, we are interested in achieving both high text controllability and whole-body appearance consistency in the generation of personalized human characters. We propose a novel framework, named SerialGen, which is a serial generation method consisting of two stages: first, a standardization stage that standardizes reference images, and then a personalized generation stage based on the standardized reference. Furthermore, we introduce two modules aimed at enhancing the standardization process. Our experimental results validate the proposed framework's ability to produce personalized images that faithfully recover the reference image's whole-body appearance while accurately responding to a wide range of text prompts. Through thorough analysis, we highlight the critical contribution of the proposed serial generation method and standardization model, evidencing enhancements in appearance consistency between reference and output images and across serial outputs generated from diverse text prompts. The term "Serial" in this work carries a double meaning: it refers to the two-stage method and also underlines our ability to generate serial images with consistent appearance throughout.
title SerialGen: Personalized Image Generation by First Standardization Then Personalization
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2412.01485