June 11, 2024, 4:50 a.m. | Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Phung

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.05641v1 Announce Type: new
Abstract: Personalizing a large-scale pretrained Text-to-Image (T2I) diffusion model is challenging as it typically struggles to make an appropriate trade-off between its training data distribution and the target distribution, i.e., learning a novel concept with only a few target images to achieve personalization (aligning with the personalized target) while preserving text editability (aligning with diverse text prompts). In this paper, we propose PaRa, an effective and efficient Parameter Rank Reduction approach for T2I model personalization by …

abstract arxiv concept cs.cv data diffusion diffusion model distribution image image diffusion images novel off personalization personalized scale text text-to-image trade trade-off training training data type via

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