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ID-Aligner: Enhancing Identity-Preserving Text-to-Image Generation with Reward Feedback Learning
April 25, 2024, 7:45 p.m. | Weifeng Chen, Jiacheng Zhang, Jie Wu, Hefeng Wu, Xuefeng Xiao, Liang Lin
cs.CV updates on arXiv.org arxiv.org
Abstract: The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention due to its wide range of application scenarios like AI portrait and advertising. While existing ID-T2I methods have demonstrated impressive results, several key challenges remain: (1) It is hard to maintain the identity characteristics of reference portraits accurately, (2) The generated images lack aesthetic appeal especially while enforcing identity retention, and (3) There is a limitation …
arxiv cs.ai cs.cv feedback identity image image generation text text-to-image type
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